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Krishobondhu : an automated system for diagnosis of paddy disease

bracu.degree.levelUndergraduate
bracu.type.groupStudent Works
datacite.rightsOpen Access
dc.contributor.advisorRahman, Dr. Mohammad Zahidur
dc.contributor.advisorAlom, Md. Zahangir
dc.contributor.authorRozario, Shovon Paulinus
dc.contributor.departmentDepartment of Computer Science and Engineering
dc.date.accessioned2014-10-02T05:13:48Z
dc.date.available2014-10-02T05:13:48Z
dc.date.copyright2014
dc.date.issued2014-09
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 43 -44).
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014.en_US
dc.description.abstractThis paper demonstrates ‘Krishokbondhu’, an automated system for the farmers to identify paddy diseases using their mobile phones. The uploaded pictures captured by the mobile phones are processed in the remote server and presented to an expert group for their opinion. Computer vision techniques are used for detection of affected spots from the image and their classification. A simple color difference based approach is followed for segmentation of the disease affected lesions. Blob detection algorithm is used for feature extraction from the segmented images where features like number of blobs in the crop, nitrogen level of the leaf, area and color values of the affected areas etc are used for classification of the diseases. Binary Search Tree is used for mapping the feature values for comparison of Euclidean distance during classification. The system allows the expert to evaluate the analysis results and provide feedbacks to the famers through a notification to their mobile phones. The mobile application has been developed for Windows Phone and the remote server application is developed using .NET framework.en_US
dc.description.degreeBachelor of Science in Computer Science and Engineering
dc.description.statementofresponsibilityShovon Paulinus Rozario
dc.format.extent49 pages
dc.identifier.otherID 11101074
dc.identifier.urihttp://hdl.handle.net/10361/3754
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University Internship reports 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.subjectComputer science and engineeringen_US
dc.subjectCrop disease management systemen_US
dc.subjectDelta Een_US
dc.subjectBlob detectionen_US
dc.subjectEuclidean distanceen_US
dc.subjectBinary search algorithmen_US
dc.titleKrishobondhu : an automated system for diagnosis of paddy diseaseen_US
dc.typeThesisen_US

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