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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characteristics. Biometric devices grant users access to programs‚ systems‚ or rooms by analyzing some biometric identifier‚ such as a fingerprint or eye pattern. Two commonly used types of biometric security devices are fingerprint readers and iris recognition systems. A fingerprint reader captures the curves and indentations of a fingerprint. Fingerprint readers can be set up to perform different functions for different fingers. For example‚ the index finger could start a program‚ and the ring finger
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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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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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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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A PROJECT REPORT ON “FINGERPRINT RECOGNITION AND IMAGE ENHANCEMENT USING MATLAB” Submitted in partial fulfillment Of the requirements for the award of the degree in BACHELOR OF TECHNOLOGY IN APPLIED ELECTRONICS AND INSTRUMENTATION ENGINEERING SUBMITTED BY: SHAKTI ABHISHEK- 0803112 SATISH GOYAL - 0803064 ROHIT DASH - 0803086 MD. IRFAN ARIF RAHMAN - 0803117 [pic] DEPARTMENT OF APPLIED ELECTRONICS AND INSTRUMENTATION ENGINEERING GANDHI INSTITUTE OF ENGINEERING AND TECHNOLOGY Biju Patnaik University
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g AUTOMATIC LICENSE PLATE RECOGNITION A PROJECT REPORT Submitted by K SIDDHARTH(11308106047) K SIVA TEJA(11308106056) D S KIRAN(11308106051) in partial fulfillment for the award of the degree of BACHELOR OF ENGINEERING In ELECTRONICS AND COMMUNICATION ENGINEERING RMK ENGINEERING COLLEGE ANNA UNIVERSITY: CHENNAI 600 025
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red light violations‚ unnecessary accidents etc. So the concept of Intelligent Traffic System was developed. In this system it was necessary to identify the vehicles that run on the road. So Automatic Number Plate Recognition (ANPR) System was developed. Automatic Number Plate Recognition (ANPR) System is essential in Intelligent Traffic Systems. ANPR Systems are made up of high-speed cameras designed to capture a photograph of each and every passing license plate‚ combined with software that analyses
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and Business Informatics - !!! DRAFT !!! Master Thesis Secure Face Recognition and User Access !!! DRAFT !!! Scientific Coordinator Prof. Ion IVAN‚ Ph.D. Graduate Valentin-Petruţ SUCIU - Bucharest 2011 - Contents Introduction 1. Machine Based Facial Detection and Recognition 1.1 Computer Vision 1.2 Object Detection 1.3 Image Quality 1.4 Facial Recognition Approaches 2. Proposed Solution 2.1 Data Preparation 2.2 Recognition Logic and Algorithms 2.3 Database Structure 2.4 Front End Applications
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Mathematical Handwriting Recognition with a Neural Network and Calculation Author: Tyler Sondag Date: 4/22/07 For Dr. Pokorny ’s CSI 490 Course Abstract The goal of this project was to create a software system that recognizes handwritten mathematical expressions and computes the answer. No special syntax or formatting was to be required for these expressions‚ since a major goal of this system was for users to be able to use the system without having to learn anything new. Support was desired for
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