Abstract This paper is about a selected few image processing applications. Optical Character Recognition is the translation of images of handwritten‚ typewritten or printed text into machine-editable text. Then I have introduced the captcha that we so frequently encounter in common websites. An algorithm trying to solve or break a captcha has been explained. Face detection is a growing and an important tool in security these days. It must be applied before face recognition. There are many
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Elementary Introduction to Image Processing Based Robots 2009 Acknowledgement P age |2 • My Senior Sourabh Sankule • My Friends Mayank and Ashish • Robotics Club‚ IIT Kanpur • Electronics Club‚ IIT Kanpur • Centre for Mechatronics‚ IIT Kanpur Ankur Agrawal IIT Kanpur P age |3 Contents Introduction ................................................................................................................ 4 MATLAB ............................................
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Image Processing Rajasekar S‚ Mohammed Nizar S ECE Department‚ Third Year RMK Engineering College raja.peak@gmail.com smohamednizar@gmail.com +919789356115 +919840515626 Abstract— This document talks about the use of image processing as one of the most crucial element of developing Futuristic Technologies in various fields. I. What is Image processing? Image processing is a method to convert an image into digital form and perform some operations on it‚ in order to get an enhanced
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The Levels of Processing ABSTRACT:- An experiment was conducted to test the levels of processing of Craik and Lockhart. This experiment aimed to find out if the three different levels of processing i.e orthographic‚ phonemic and semantic will affect the recall of words. Participants who were 109 first year undergraduate psychology students were presented with 30 list of words one at a time which comprised of the three different levels processing and at the end were given free recall. The data
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process it into useful information (output) and stored it away (in a secondary storage device) for safekeeping or later reuse. The processing input to output is directly by the software but performed by the hardware. To function‚ a computer system requires four main aspect of data handling: Input Processing Output Storage Secondary Storage Input Processing
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proposed approach. These results are also compared to other filters by numerical measures and visual inspection. Keywords: AFuzzy sets‚ Fuzzy filters‚ Fuzzy smoothing‚ Fuzzy derivative 1. INTRODUCTION The application of fuzzy techniques in image processing is a promising research field. Fuzzy techniques have already been applied in several domains of image
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Chapter 4 Downstream Processing Objectives Student should be able to Define filtration‚ centrifugation‚ cell disruption‚ solvent extraction‚ chromatography‚ membrane process‚ action of force field‚ evaporation & drying Explain briefly on the concept of each topics stated above List out the uses & importance of each topic stated Introduction Each stage in the overall recovery procedure is strongly dependent on the history & quality of the biological production process. Maximization of
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Abstract – Image Processing Algorithms are the basis for Image Computer Analysis and Machine Vision. Employing a theoretical foundation – Image Algebra – and powerful development tools – Visual C++‚ Visual Fortran‚ Visual Basic‚ and Visual Java – high-level and efficient Computer Vision Techniques have been developed. This paper analyzes different Image Processing Algorithms by classifying them in logical groups. In addition‚ specific methods are presented illustrating the application of
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2 Areas of data processing 1. Business Data processing (BDP) . Business data processing is characterized by the need to establish‚ retain‚ and process files of data for producing useful information. Generally‚ it involves a large volume of input data‚ limited arithmetical operations‚ and a relatively large volume of output. For example‚ a large retail store must maintain a record for each customer who purchases on account‚ update the balance owned on each account‚ and a periodically present a
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video sequences. The fourth video sequence reached 97.6% and the third 90.6%. In TEST 2‚ the iris detection was above 96% in all five video sequences with two above 99.7% and two at 100%. Face size estimation is also above 99.9%. The average processing time of our method was 0.02 s per frame. Thus‚ the proposed method can process frames at a rate near to 50 frames/s‚ and therefore‚ is applicable in real time in a standard personal computer (PC 1.8 GHz). Index Terms—Anthropometric templates
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