1. INTRODUCTION: Pattern recognition has become a very interesting topic for researchers during last few decades. Handwriting recognition is very challenging area of pattern recognition with various practical applications. There are many applications of this form of recognition. Like postal code verification‚ vehicle number plate recognition‚ bank cheque processing‚ Assigning ZIP Codes to letter mail‚ automatic reading of area code and address from the letter‚ various data form processing etc. MEETEILON
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Project Report On LICENSE PLATE RECOGNITION SYSTEM PROJECT GROUP MEMBERS A. NISHANTH J. VISHWESH NACHIKET VASANT VAIDYA NAVEEN SUKUMAR TAPPETA R. ANAND UNDER THE GUIDANCE OF PROF. S. R. SATHE DEPARTMENT OF COMPUTER SCIENCE VISVESVARAYA NATIONAL INSTITUTE OF TECHNOLOGY NAGPUR 2008-2009 DEPARTMENT OF COMPUTER SCIENCE VISVESVARAYA NATIONAL INSTITUTE OF TECHNOLOGY NAGPUR 2008-09 CERTIFICATE This Is To Certify That A. Nishanth J. Vishwesh Nachiket Vasant
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Optical Character Recognition for Cursive Handwriting Nafiz Arica‚ Student Member‚ IEEE‚ and Fatos T. Yarman-Vural‚ Senior Member‚ IEEE AbstractÐIn this paper‚ a new analytic scheme‚ which uses a sequence of segmentation and recognition algorithms‚ is proposed for offline cursive handwriting recognition problem. First‚ some global parameters‚ such as slant angle‚ baselines‚ and stroke width and height are estimated. Second‚ a segmentation method finds character segmentation paths by combining gray
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SPEECH RECOGNITION TECHNOLOGY Final Research Project Health Care Information System 649 December 02‚ 2012 Abstract This research paper presents an overview of speech recognition technology system development and applications. My research begins with the definition of the speech recognition system and continues on to exploring its usages‚ benefits
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MASTER ’S THESIS Face Recognition in Mobile Devices Mattias Junered Luleå University of Technology MSc Programmes in Engineering M edia Technology D epartment of Computer Science and Electrical Engineering Division of Signal Processing 2010:040 CIV - ISSN: 1402-1617 - ISRN: LTU-EX--10/040--SE Face Recognition in Mobile Devices Mattias Junered Luleå University of Technology March 2‚ 2010 Abstract Recent technological advancements have made face recognition a very viable identification
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looking at blood splatter‚ the forensic technician can conclude an estimated guess to the weapon used‚ the height of the person‚ whether it was foul play or not‚ and even if it was passive patterns or projected patterns. Blood splatter analysis becomes important when recreating a crime scene (Peschel). Bloodstain pattern analysis comes into play; and that is the interpretation of bloodstains at a crime scene in order to recreate the actions that caused the bloodshed (“A Simplified Guide”). High-speed
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Getting Started in CHART PATTERNS Thomas N. Bulkowski John Wiley & Sons‚ Inc. Getting Started in CHART PATTERNS The Getting Started In Series Getting Started in Online Day Trading by Kassandra Bentley Getting Started in Asset Allocation by Bill Bresnan and Eric P. Gelb Getting Started in Online Investing by David L. Brown and Kassandra Bentley Getting Started in Investment Clubs by Marsha Bertrand Getting Started in Internet Auctions by Alan Elliott Getting Started in Stocks by
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crime scenes to laboratory work. Limited analysis can be performed using just photography. The analysis of blood includes two phases: Pattern analysis- this includes interpreting the shape and distribution of the bloodstain and drawing conclusions on the mechanisms that have caused the bloodshed. Reconstruction- by using the data obtained from pattern analysis analysts must determine the location of the victim and the suspect during the bloodshed cause‚ where the blood originated‚ whether
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Touchless biometric products; Europe follows shortly The concept of gesture recognition has come into major attention with the launch of Microsoft’s Kinect in 2010. The new and enhanced user experience offered by various technologies has gathered interest from a number of OEMs across many applications. This has resulted in the launch of products ranging from smart TVs to Smartphones that integrate with gesture recognition technologies. The report’s detailed segmentation by technology‚ by applications
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face recognition is as old as computer vision and both because of the practical importance of the topic and theoretical interest from cognitive science. Face recognition is not the only method of recognising other people. Even humans between each other use senses in order to recognise others. Machines have a wider range for recognition purposes‚ which use thinks such as fingerprints‚ or iris scans. Despite the fact that these methods of identification can be more accurate‚ face recognition has always
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