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dc.contributor.advisorAli, Md. Haidar
dc.contributor.authorJoyee, Faiza Nuzhat
dc.contributor.authorMahsa, Nuzhat Ashraf
dc.contributor.authorReza, Zarreen Naowal
dc.date.accessioned2016-05-22T10:46:44Z
dc.date.available2016-05-22T10:46:44Z
dc.date.copyright2016
dc.date.issued2016-04-21
dc.identifier.otherID 10101006
dc.identifier.otherID 12101009
dc.identifier.otherID 12101072
dc.identifier.urihttp://hdl.handle.net/10361/5303
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2016.en_US
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 47).
dc.description.abstractIn our research, we have implemented an automated system for disease detection of jute plants using image analysis and machine learning. We have also integrated this system with a mobile application for Android phones to serve the farmers where they get benefitted by identifying the diseases correctly and taking measures accordingly. At first, an image of the defected jute plant has been taken with the camera of the mobile phone. The farmers then just have to send the image to our server by selecting the options provided on the application. The image has been analyzed in the server where the plant’s affected parts will be segmented using hue-based segmentation method, features for the texture analysis has been extracted using color co-occurrence methodology and comparing with our pre-defined database the disease is identified and classified using SVM classifier. At the final step, the classification result along with the necessary control measurement has been sent back to the user through the application on the phone.en_US
dc.description.statementofresponsibilityFaiza Nuzhat Joyee
dc.description.statementofresponsibilityNuzhat Ashraf Mahsa
dc.description.statementofresponsibilityZarreen Naowal Reza
dc.format.extent47 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.subjectCSEen_US
dc.subjectComputer science and engineeringen_US
dc.subjectJute plant diseaseen_US
dc.subjectTexture analysisen_US
dc.subjectHue based segmentationen_US
dc.subjectSVM classifieren_US
dc.titleAutomated system for detecting jute plant disease using image processing and machine learning integrated with mobile applicationen_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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