Love : The Eternal Bliss


This article was first published in Anubhooti, Hostel-1 Annual Magazine 2012-13 , IIT Bombay.

Its made a bit ugly here :(

This article describes a few practical aspects on living a cheerful and happy life along with making important contributions and impacts to others lives by means of Love.

“What worth is a life, if it is of no use to others?” [I have heard it often, but don't remember it where]

This demands purity and; purity demands thinking of others as not other than you. This aspect is generally very handy whenever one is in a confused state and hence unable to make decisions. But isn’t this a very abstract thought? Yes, it is indeed an abstract thought and therefore only people who have become self-aware i.e. have achieved self realization can exactly feel this bliss of being able to take a decision without any second thoughts. So, how does this help common man? One of the practical tool for achieving similar result is “Do unto others what you would have them do to you”. [A Bible verse]

When people start putting themselves in others position, the result is a self compassionate relationship. With compassion comes Love. And thus, people become aligned towards “Universal Love”.

What is this Universal Love?

Universal Love is being conscious and loving at the same time. When you experience universal love you understand the action of love.It is an expression of harmony of the totality. Everything is in harmony with everything else. Thus, there is no conflict anywhere. This is also termed as becoming one with the god or the nature. [~A.H.Almaas]

Universal Love can only be achieved without the presence of personality. WIth personality comes the ego and therefore, ego and love cannot exist together. Ego always creates intersecting circles and hence, the confusion in making decisions.

Perhaps, one of the most poignant sufferrings in the society is the failure of human relationships. We often see so many cases of strained and failed relationships around us and possibly in our own lives as well.

The desire of relationship is very much intrinsic to our nature. The vedas explain that every living being has an eternal relationship with God. We cannot be satisfied if we forget God and offer our love to someone else because only God knows how to reciprocate our love. [Read this for more detail  http://news.iskcon.com/node/4189 ]

This arouses one doubt; does offering our love to God mean we cannot love other people? The answer is just the opposite: With God as the center of all our relationships it becomes blissful. If it is not the case, then it is not love; rather it is mutual exploitation for selfish needs. Thus, if we can centre the relationship on God then they become selfless and deeply rewarding.

“If you judge people you have no time to love them” ~ Mother Teresa.

Online Courses


online learning

Fig.1 : Online Learning

I recently(fall’2011) happened to complete 2 online courses(3 courses were offered) namely, Machine Learning(Stanford) and Artificial Intelligence(Knowit and Stanford). Although I liked ML course immensely but I think AI course fell very much short of my expectations. But AI team seems to already know this and therefore they have offered 2 practical courses : “Building Search Engine” and “Programming a Robotic car”. Check this: http://www.udacity.com/. Nevertheless its a great initiative by the Stanford which I think makes it bigger than OCW MIT. Seeing the impact and vision of Stanford’s online courses , MIT launched similar program called MITx. Also, stanford taking it further has offered 16 more courses this spring’2012 semester. Check http://www.class-central.com/ . These initiatives will benefit the motivated students who are unable to build solid fundamentals due to factors like lack of good teachers, lack of mobility/infrastructure, etc.  Much Appreciated initiative!!

Khanacademy is another venture which looks into online lectures for primary classes, higher classes and many more. Its not-for-profit and visions “A free world-class education for anyone anywhere”. My niece(class 8) and my nephew(class 6) also refer to the lectures on science, maths, etc. and they really love lucid explanations and thus enables them enjoy doing exercises even more.  Its really huge!!  Kudos to Salman Khan and his team.

By now you would guessed that my primary interest is machine learning and artificial intelligence. Some of the excellent resources for the same are here.

Computer Networking Foundations


Converted a page to post
People generally have a notion that the Computer Networking is all about programming but they seem to forget that programming is just a part[and of course an art]. Programming Algorithms, implementing protocols, monitoring network etc. are only a few aspects of computer networking [although essential]. Programming has now become essential in everything you do and is just a tool to meet the ends and hence I wouldn’t talk about programming anymore in this page as it is something that i have done a lot and am not interested anymore. But, what I am interested in is the underlying ideas, which are generally provided in the research papers and are hard to grasp as the mathematical/theoretical stuffs keep floating around all over the paper. Therefore, in order to understand how the networking works as well as have a better idea of the papers it becomes quite essential for the various people in the networking domain to have some level of these mathematics. Let me first list down these, so called “mathematical tools”, :

  1. Theory of Probability and Stochastic Processes.
  2. Linear Algebra
  3. Non-linear & Linear Programming [Optimization]
  4. Markov Chains & Queuing Theory
  5. Graph theory
  6. Game Theory [Optional]
  7. Information & Coding Theory

Dependency graph would something look like this:

 

dependendency_graph

dependendency_graph

In the dependency graph, the higher a number is placed, more important it is. Therefore, one needs to grasp the concepts of [1] and [2] primarily as they act as the pillars for the entire networking. And, once these two are mastered, one can build upon it the concepts of optimization, markov chains and queuing theory. “Graph theory” doesn’t need any prerequisite, neither does Game theory. But in Game theory, some elementary matrix algebra is helpful. Having some knowledge of Information and Coding theory might brings in some innovation in the network research one is pursuing as it tries to look at networking with a different perspective. Most importantly, it tells you the limit so that you don’t incessantly foolishly try to be too ambitious in achieving which is beyond the limit.

In this blog, I’ll be starting with an introduction to probability theory and stochastic processes and will also be mentioning some good reference books for different kinds of readers. I wouldn’t be covering linear algebra since the lecture video of Prof. Gilbert Strang is readily available and infact is the best resource one could find. Click here for videos. For solving out problems in linear algebra, one could follow his simple to understand book titled ” Linear Algebra and its Applications”. I’ll also chalk out the plans on how to take it further, especially for optimization and queuing theory during my vacation in May-July 2010. By the way, something which inspired me in this direction is this page by Prof S. Keshav sometime back . Some of the introduction has been covered in Prof. Keshav’s videos. I am in total awe of prof’s ability to present even the complex stuffs with such elegance and lucidity. But, I’ll try to give the pointers for the above mentioned stuffs according to my own understanding and try to make it easier for the intended viewers who are having an understanding at different levels.

Wireless Sensor Networks: Applications & Roadmap


This article is part of the article on work done in SPANN LAB, IIT Bombay(Prof U.B.Desai, Prof S.N.Merchant)

Wireless Sensor Networks (WSNs) have become one of the most interesting areas of research in the  past  few years primarily due to its large number of potential applications. WSN is an enabler technology, many believe that it can revolutionize ICT(Information and Communication Technologies), the way microprocessor revolutionized chip technology nearly 30 years ago. The proliferation in MicroElectro-Mechanical Systems (MEMS) technology has facilitated the development of smart sensors. These recent advances in Wireless Sensor Networks (WSN’s) have also lead to rapid development of real time applications. In this article we take a tour on how WSNs have evolved over the last decade with emphasis on the applications. In 2003, Technology Review from MIT, listed WSN on the top, among 10 emerging technologies that would impact our future.

The increasing interest in wireless sensor networks can be promptly understood simply by thinking about what they essentially are: a large number of self-powered small sensing  nodes which gather information or detect special events and communicate in a wireless fashion, with the end goal of handing over their processed data to a base station. There are three main components in a WSN: the sensor, the processor, and the radio for wireless communication. Processor and Radio technology are reasonably mature. Nevertheless, cost is still a major consideration for large scale deployment. The  inherent nature of WSNs  makes them deployable  in a  variety of circumstances. They  have the potential to be everywhere, on roads, in our homes and offices(smart homes), forests, battlefields, disaster struck areas, and even underwaters. This very pervasive nature leads us to “everyware” phenomenon of ubiquitous computing. Today, we have entered the third wireless revolution,”Internet of Things”. The third wave is utilizing wireless sense and control technology to  bridge the gap between the physical world of humans and the virtual world of electronics. The dream is to automatically monitor and predict or respond to forest fires, avalanches, land slides, earthquake, hurricanes, traffic, hospitals  and much more over wide areas and with thousands of sensors.  It has come in reaching grasp due to the development of Wireless  Sensor Networks (WSN) more oftenly called Ubiquitous Sensor Networks (USN).  If we look back, a lot of work have been done in the field of protocols, collaborative information processing, dedicated OS like Tiny OS, dedicated database systems like Tiny DB, programming languages like nesC, 802.15.4 standardization in form of Zigbee, and large number of test deployments. Also, major initiatives in WSN R&D have been taken by MNCs like Microsoft(Project Genome), Intel(WISP), IBM(IBM Zurich Sensor System lab and Testbeds), SUN Microsystems(SPOT), etc.

Sensor networks provide endless opportunities, but at the same time pose formidable challenges, which include deployment, localization, self-organization, navigation and control, coverage, energy, maintenance, and data processing.  The fact that energy is a scarce and usually non-renewable resource,  power consumption is a central design consideration for wireless sensor networks whether they are powered using batteries or energy harvesters. However, recent advances in low power VLSI, embedded computing, communication hardware, and in general, the convergence of computing and communications, are making this emerging technology a reality in terms of processing, memory and energy. In general, WSNs are deployed using a non-renewable, but there have been applications like pervasive sensor environment(described later) which uses renewable source of energy, here, solar power. In many current projects, applications are executing on the bare hardware without a separate operating system component. Hence, at this stage of WSN technology it is not clear on which basis future middleware for WSN can typically be built. Another key challenge in WSN is the middleware. Middleware as the name suggests, sits right in between the operating system and the application. The main purpose of middleware for sensor networks is to support the development, maintenance, deployment, and execution of sensing-based applications. Currently, programmers deal with too many low levels details regarding sensing and node-to-node communication and the programming abstractions provided by middleware become a key aspect in its pursuit. Middleware also plays a very crucial role in leading to pervasive sensor systems. Ad-hoc sensor networks although related to WSNs but are very different in terms of energy supply, number of sensor nodes, computational capabilities, memory and global identification. In this article we limit ourselves to WSN.

Since the inception of “low power wireless integrated microsensors” in 1994, a DARPA funded research, WSNs have become a rage globally . In India, the technical institues were the first to take the onus of making contributions to this emerging field by doing a cutting-edge research which was soon to catch attention of government and public in solving real-world problems.

The major WSN projects undertaken in India were:
•    DRDO (Defense Research and Development Organization) project on theoretical aspect, mote development and deployment (with IISc.)
•    WSN for critical emergency applications like landslide predictions (Amrita University, IIT-Bombay, IIT-Delhi, IIT-Kgp)
•    WSN for tracking and monitoring in underground mines (Central Mining Research Institute)
•    Underwater wireless sensor networks (IIT-Bombay, Naval Physical & Oceanographic Laboratory)
•    WSN for Agriculture (IISc, IIT-Bombay)
•    Pollution monitoring (IIT-Delhi, IIM-Kolkata, IIT-Kgp, IIT-Bombay, IIT-Hyderabad)
•    WSN for Biomed (IIT-Bombay)
•    Many IITs also have WSN testbeds.

WSN are a great enabler for component manufacturers, system integrators, software services providers, OEMs, application developers and other end users.
WSN also started transiting from active academic research to industry. This emerging area has inspired many start-up companies like Virtual Electronics Company (Roorkee) , Dreamajax Technologies(Bangalore), Airbee Wireless (India), Virtualwire (Delhi), etc. and numerous small firms specialising in sensors. Big players like Infosys, TCS and Wipro  also value this key technology. Infosys has a dedicated R&D labs Convergence and SETLabs, which pursues R&D in  pervasive computing and wireless sensor networks. TCS Innovation Lab in Mumbai expertises in wireless technology (mKrishi). Wipro and Infosys have been an active partner in the pervasive sensor environment project under the umbrella of IU-ATC(Indo-UK Advance Technology Centre) a 9.2 million pound project.

Here we describe some important path-breaking WSN applications which present a great social and economic impact:

1. Senslide: Landslide Predictions
Senslide is a novel distributed sensor system for predicting landslides. The idea of predicting landslides using wireless sensor networks was originally conceived at the SPANN Lab in the EE Department IIT Bombay. It arose out of a need to mitigate the damage caused by landslides to human lives and to the railway network in the hilly regions of Western India. With support from Microsoft Research India and collaboration from the Earth Science Department IIT Bombay, Senslide became a joint research project among these three research groups. Having an inter-disciplinary team with expertise in each area has been invaluable in coming up with a solution. The system uses a combination of techniques from Earth Sciences, signal processing, and distributed systems and fault-tolerance.
A unique feature of the design is that it combines several distributed systems techniques to deal with the complexities of a distributed sensor network environment where connectivity is poor and power budgets are very constrained, while satisfying real-world requirements of safety.  Senslide uses an array of inexpensive single-axis strain gauges connected to cheap nodes (specifically, TelosB motes), each with a CPU, battery, and a wireless transmitter. These sensors make point measurements at various parts of a rock, but make no attempt at measuring the relative motion between rocks. The strategy is based on the simple observation that rock slides occur because of increased strain in the rocks. Thus, by measuring the cause of the landslide, one can predict landslides as easily as if one would be measuring the incipient relative movement of rocks.

SensSlide

Figure 1: Senslide, Landslide Prediction

2. Landslide Predictions
Landslide predictions have been carried out in full pursuit at IIT-Bombay and Amrita Center for Wireless Networks and Applications(Amrita-WNA). Known for its successful completion of the Indo-European WINSOC Project, Amrita-WNA is recognized worldwide today for its deployment of the first-ever wireless sensor network system for predicting landslides. The system uses wireless sensor technology to provide advance warning of an impending landslide disaster, facilitating evacuation and disaster management. The Government of India has shown interest to deploy this system in all landslide prone areas including the Himalayas and the Konkan Region. India’s first ever cutting edge wireless sensor network system, designed to detect landslides at least 24 hours ahead of its occurrence, has been set up at Munnar in the high range Idukki district of Kerala where eight persons had lost their lives in 2005 landslides.
3. Pervasive Sensor Environment
Pervasive Sensor Environment is an ongoing active project for environment monitoring under the umbrella of IU-ATC funding by Department of Science and Technology, Government of India. This application is of significant social and economic interest and is envisioned to be able to support a diverse range of sensor-network based services across a scalable infrastructure. Its broad aims are:
•    Distributed pollution level measurement.
Sensing elements placed along roads, in buildings and in watercourses will provide information about both atmospheric pollution and the threats to health from contaminants in materials that are vital to health. This links directly to WHO and Global Health initiatives of the UN.
•    Traffic monitoring.
Traffic levels are set to grow, and both the nature of the movement patterns experienced by cars and the quality of the roads are of importance to both drivers and the authorities associated with road planning and maintenance.
In pursuit of achieving the above desired goals, it also tries to solve other intermittent problems like low cost mote development, scalable network protocols with power-aware paradigm, middleware development, Data warehousing for the scientific pollution repository, and a context-framework for context-based pervasive computing. The real-time environment monitoring has been carried out using Libelium Waspmotes on a smaller scale in Hyderabad and Mumbai city. The motes are equipped with solar panel, GPS, gas sensors namely, CO2, O2, NO2 and CO, and other sensors namely, temperature, humidity and air pressure. Considering the full scale deployment cost, low cost motes are being developed at IIT-Hyderabad which challenges the pricing of the motes present in market by 1/10th.The data warehouse in IIT-Bombay has been developed using Microsoft SQL Server 2005 including SSAS and SSIS. The data insights are obtained using various SSAS built-in data mining algorithms like association rule mining, decision tree analysis, and clustering. Ambient Air Quality Index (AQI) standardizations are also refined in the process.

 

pervasive sensor network

Figure 2: Pervasive Sensor Environment, Sensor Deployment in Bombay

 

overall system

Figure 3: Pervasive Sensor Environment, Ongoing Work

4. AgriSens: WSN for Precision Agriculture
AgriSens has been a revolutionary Agro-based WSN conceptualized and developed in IIT-Bombay. This project had been funded by Department of Information Technology, Government of India.  This application is a revolution in the sense that it overcomes the technical and social challenges of precision farming systems in India using WSN. The agriculture system is considered to be a complex interaction of seed, soil, water, fertilizer and pesticides. Exploitation of agricultural resources to bridge the gap in supply/demand is leading to the resource degradation and subsequent decline in crop yields. This calls for optimal utilization of the resources for managing the agricultural system. Precision farming, an information and technology based farm management system, is to identify, analyze and manage variability within field for optimum profitability, sustainability and protection of the resources. WSN one among many technologies i.e. (Remote Sensing, Global Positioning System (GPS) and Geographical Information System (GIS)) practiced for precision farming, is found to be suitable for collecting the real time data of different parameters pertaining to weather, crop and soil and thereby helpful in developing solutions for majority of the agricultural processes related to application of water, fertilizer, pesticides etc.
A case study built through a 2 year research project on deployment of WSN in green house at pilot scale and at grapevine in NASHIK district (India) has enabled testing its robustness and permitting to evaluate the input requirement i.e. water requirement and need of pesticides. Initial deployment of AgriSens was done at green house, IIT Bombay mainly for testing the ruggedness of the system for crops grown under controlled conditions. Once the technical feasibility established, it was extended to larger scale in vineyard. An embedded gateway base station performed elementary data aggregation and transmitted the sensory data to Agri-information server via GPRS. The server was situated at the SPANN Lab, Department of Electrical Engineering, IIT-Bombay i.e. about 200 km away from the field. The server also supported a real time updated web-interface giving details about the measured agri-parameters. The infection index was estimated using already existing semi-empirical models i.e. Logistic and Generalized Beta models for prediction of powdery mildew in Grapes. The outputs of the models were “infection index value” and the “timing of the different infection events”.  It was observed that high risk of infection was corroborated with almost 11 ± 1 hrs of wetness duration with the average ambient temperature of 25 degree Celsius.

 

Agrisens

Figure 4: AgriSens, Sensor deployment at Sule Vineyard, NASHIK(India)

5. Body Area Networks.
The rapid growth in physiological sensors, low power integrated circuits and wireless communication has enabled a new generation of wireless sensor networks. These wireless sensor networks are used to monitor traffic, crops, infrastructure and health. The body area network field is an interdisciplinary area which could allow inexpensive and continuous health monitoring with real-time updates of medical records via Internet. A number of intelligent physiological sensors can be integrated into a wearable wireless body area network, which can be used for computer assisted rehabilitation or early detection of medical conditions.
At IIT-Bombay, physiological body signals are extracted via sensors fabricated of textiles, which are integrated with the attire of the subject. These sensors transmit the signal through specially formulated conductive fabric fibers, which act as conducting wires in our WBAN Architecture to an On Body Transmission Circuit (OBTC). The multiple sensors are interconnected the OBTC based on the applications opted by the user and the power requirement of the WBAN. The OBTC steps up the signal to the UWB operating frequency in range of 3.1 to 10.6 GHz and transmits it to On Body textile UWB antenna. The OBTC is also innovatively designed to power the entire system, by absorbing heat emitted by the subject body. Incorporation of thermoelectric generators using body heat typically shows a drop in generated power when the ambient temperature is in range of the body temperature. The connections between the OBTC and Textile Antennas are also made up of same conductive fibers that connect the sensors to OBTC. An ideal testbed is set up for subject monitoring devoid of any metallic components with the sensor integrated with the textile body patch. The UWB Textile antennas on the body send or receive signals through smart phones. The transmitted signals are received at the remote health monitoring station. This approach would allow one to assess quality of movement in the home and community settings and feed this information back into the clinical decision process to optimize the rehabilitation intervention on an individual basis. With the Machine Learning tools the engine provides an automatic diagnostic system.
6. Underwater Sensors
Underwater Sensor Networks (UWSN) although have potential for broad range of applications like pollution monitoring, assisted navigation, disaster prevention, seismic monitoring, etc. but the challenges are even more daunting. The UWSN exploration at IIT-Bombay in collaboration with Naval Physical & Oceanographic Laboratory(NPOL) came up with a novel approach to overcome the challenges by proposing Energy Optimized Path Unaware layered routing protocol (PULRP). PULRP is an on the fly distributed algorithm, so mobility and loss of connectivity due to multipath are taken care of along with localization and time synchronization . PULRP considers energy parameter for potential relay node selection and is an energy optimized algorithm. IIT Bombay also has testbed for UWSNs .

underwater sensors

Figure 5: UWSN, Network Architecture

7. Electronic Toll Collection
Electronic Toll Collection System is combination of techniques and technologies that allows vehicles to pass through a toll facility without requiring any action by driver (i.e. stopping at the toll plazas to pay cash). This project had been funded by Department of Information Technology, Government of India. ETC starts with the capability to detect the presence of a vehicle. Based on such detection, vehicles are classified in different categories. The information of vehicle classification is used to deduct the tolling amount from the account of user. Electronic Toll Collection System consists of three components Automatic Vehicle identification system, Automatic Vehicle Classification System, and Enforcement system. Wireless communication, sensors and a computerized system uniquely identifies each vehicle to electronically collect the toll. Important aspect of this architecture is it requires very less infrastructure. Electronic Toll Collection is implemented using Motes for On-board Unit and Roadside Unit programmed with Tiny OS, and server programmed using SQL. Implemented Electronic Toll Collection using MARWELL USB 0800 Cards for Onboard Unit, Road-side Unit, and Server, Communication between these units was established using UDP Socket Programming. Server Uses SQL for toll collection.

electronic toll collection

Figure 6: Electronic Toll Collection, Architecture

Conclusion:
WSNs are biggest proponents with regard to the third wave in computing. i.e.; Ubiquitous computing and it’s subsuming. First were mainframes, each shared by lots of people. Now we are in the fading end of personal computing era, person and machine staring uneasily at each other across the desktop. Ubiquitous computing has just entered, or the age of calm technology, when technology recedes into the background of our lives. WSNs have indeed made a huge social and economic impact and the exploration by the technical institutes especially IIT -Bombay had been more than worth in creating real-time applications and testbeds all along the way.

2011 in review


The WordPress.com stats helper monkeys prepared a 2011 annual report for this blog.

Here’s an excerpt:

A New York City subway train holds 1,200 people. This blog was viewed about 5,700 times in 2011. If it were a NYC subway train, it would take about 5 trips to carry that many people.

Click here to see the complete report.

R-ebook : Dewarping scanned e-books


R-ebook

R-ebook

CS 663, Digita Image Processing , Course Project, Autumn 2010

Group: iRoll

Instructor: Prof. Sharat Chandran

Members (In Alphabetical Order): Feroz, Mayur, Nikhil, Rahul, Rajath

Problem Statement

The aim of the project is to make the scanned documents more readable. Scanned documents are generally prone to noise and the various problems can be roughly listed as below,

  1. Incorrect Orientation.
  2. Need for Image enhancement.
  3. Handwritten text outside the text region
  4. Skewed lines

We are applying various cleanup methods to make the scanned document more legible to read.

Figure below shows a typical scanned image along with the output .

Input :

Input Image

Input Image

Output :

final output

final output

Implementation

An overview of implementation is given below in the flow model.

R-ebook Flow model:

block diag

Block Diagram

1. Shade and noise removal

Initial noise removal is done using basic image processing techniques like erosion, dilation, binarization and hole filing operations. Noise outside the text region can be completely removed after detecting the text region.

Edge Detection(using ImageJ)
Input :

stage1_b

stage1_b

Edge Detected Output :

Edge detected output

Edge detected output

Orientation correction

Here the input image is edge detected and assumed to be oriented not more than 45 degree on either side. Initially this image is rotated anticlockwise by 45 degrees . Then, it is rotated by 1 degree incrementally upto 45 degrees clockwise of the original input and corresponding horizontal projections are also calculated. The angle at which it gives the maximum variance of the horizontal projections is the correct orientation.

Thus the input image is then rotated to the correct orientation.

Input Image :

orient_input

orient_input

Orientation corrected Image :

orient_output

orient_output

Detection of text box

Detection of text box is used to accomplish the task of identifying word regions. Initially erosion, dilation and hole-filling is applied with a pre-defined filters. Secondly, Connected component analysis (CC) is done to identify individual blocks, these text blocks are typically words.  Unwanted part of the scanned document is removed by using the properties of a text region like height-width aspect ratio, extent( Scalar that specifies the ratio of pixels in the region to pixels in the total bounding box ),etc.

Figure below shows the input image, intermediate result after dilation and erosion and the final image after using connected component analysis.

text region detection

text region detection

Text block detection
CC Output

Connected Component output

Connected Component output

Detection of text rows and tracking the lines

Now, once these text blocks are detected , it is further analyzed to identify the text rows by grouping of words in each row. The line start, line end, CC labels and width of the line are the parameters used for grouping of these text blocks into a line. We also make use of 2 imortant properties of individual bounding box(alternatively, text blocks) — centroid and extrema. We thus create a look-up table(LUT) with line numbers and a list of text blocks associated with each row.

Dewarping of lines

The centroids of each text block of a row are interpolated to trace the entire line. This is iterated over the rows. Each row is labelled according to their ‘y’ co-ordinate. These y co-ordinates are taken from the unwarped section.

Interpolation of rows

Interpolation of rows

Now, the intermediate line between the rows are also obtained by vertical interpolation. This corresponds to the position of each pixel to be shifted for the dewarped position. These pixels are moved to the desired position. An inverse mapping table is created , which provides the coordinates to which each pixel has to be shifted as shown below.

inverse map

inverse map

This entire process is based on interpolation. Intermediate gaps(if any) are also interpolated vertically at the output side.

Pledge

This is a course project for the course Digital Image Processing at Indian Institute of Technology Bombay. Therefore we are pledging on our honour that we have not given or received any unauthorized assistance in this project or any previous homework.


Reference:

[1]Correcting Book Binding Distortion in Scanned Documents, Rafael Dueire Lins et.al,Hewlett Packard Labs (2010).

[2]Enhancing Readability of Scanned Picture Books, Chang Hu et.al, Computer Science Department,University of Maryland .

[3]Enhancing Readability of Scanned Picture Books, Chang Hu et.al, Computer Science Department,University of Maryland .

2010 in review


The stats helper monkeys at WordPress.com mulled over how this blog did in 2010, and here’s a high level summary of its overall blog health:

Healthy blog!

The Blog-Health-o-Meter™ reads Fresher than ever.

Crunchy numbers

Featured image

A Boeing 747-400 passenger jet can hold 416 passengers. This blog was viewed about 3,000 times in 2010. That’s about 7 full 747s.

In 2010, there were 13 new posts, growing the total archive of this blog to 18 posts. There were 20 pictures uploaded, taking up a total of 3mb. That’s about 2 pictures per month.

The busiest day of the year was December 3rd with 44 views. The most popular post that day was Computer Networking… Getting the basics right.

Where did they come from?

The top referring sites in 2010 were google.co.in, facebook.com, lmodules.com, cordless-homephone.info, and linkedin.com.

Some visitors came searching, mostly for whiteswami, top 10 algorithms of the 20th century, probability+scilab, gate cs essentials, and fingerprint core point code.

Attractions in 2010

These are the posts and pages that got the most views in 2010.

1

Computer Networking… Getting the basics right April 2010
2 comments

2

GATE CS Tips !! April 2010
9 comments

3

GATE IIT Admissions May 2010
2 comments

4

Fingerprint Recognition using DCT November 2009
13 comments

5

Fedora Post Installation Setting at IIT Bombay October 2009

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