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dc.contributor.advisorUddin, Jia
dc.contributor.authorArko, Fahmid Nasif
dc.contributor.authorTabassum, Nujhat
dc.contributor.authorTrisha, Taposhi Rabeya
dc.contributor.authorAhmed, Fariha
dc.date.accessioned2017-05-31T06:58:49Z
dc.date.available2017-05-31T06:58:49Z
dc.date.copyright2017
dc.date.issued4/18/2017
dc.identifier.otherID 13101087
dc.identifier.otherID 13101027
dc.identifier.otherID 13101163
dc.identifier.otherID 13101024
dc.identifier.urihttp://hdl.handle.net/10361/8216
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 27-29).
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.en_US
dc.description.abstractInstant feedback on sign language can greatly improve sign language interpretation. In this project we plan to use efficient methods to detect the hand correctly using skin detection algorithm and removing all noise using MATLAB and classify the image according to the sign gesture performed. In this paper, we propose an image processing based model which will interpret Bangla Sign Language. The purpose of this model is to find Bangla Sign Language recognition accuracy. The model will detect the skin color of every type using 𝑌𝐶𝐵𝐶𝑅 algorithm and use Bag of features for feature extraction and Support Vector Machine (SVM) for training and evaluation. To validate our proposed model, we used our own dataset of Bangla Sign Languages using hand gestures of both male and female. The average accuracy we got from evaluation set is 86%.en_US
dc.description.statementofresponsibilityFahmid Nasif Arko
dc.description.statementofresponsibilityNujhat Tabassum
dc.description.statementofresponsibilityTaposhi Rabeya Trisha
dc.description.statementofresponsibilityFariha Ahmed
dc.format.extent29 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectImage processingen_US
dc.subjectSign languageen_US
dc.titleBangla sign language interpretation using image processingen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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