{"_buckets": {"deposit": "8b865bb9-e91c-45e6-9c63-bdd1b866ee3b"}, "_deposit": {"id": "4303", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4303"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4303", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Content-Based Image Classification and Retrieval using Support Vector Machine", "subitem_1551255648112": "en_US"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Image search is more efficient for managing a wide range of imagedatabases. Content-based image retrieval (CBIR) is one of the image retrievaltechniques in which users use the visual characteristics of images such as color,shape and texture, etc. It permits the end user to give a query image in order toretrieve the image stored in the database based on the similarity to the query image.The system extracts the features of the query image, searches the database for imageswith similar features, and exhibits relevant images to the user in order of similarity tothe query. Many CBIR systems have been developed to compare, analyze, and searchimages based on one or more of these features. This system is implemented as animage retrieval system combining visual content features and a support vectormachine (SVM) classification.First, the system extracts the features of images from dataset with color autocorrelogram, color moment and gabor wavelet for the training phrase. When the userinput query image, the system extracts features with these feature extraction methodsin the testing phrase. And then, the system applies support vector machine (SVM)classifier to classify the image. After that, the system compares feature vectorsbetween the query image and image dataset. Finally, the system retrieves therelevant image with query image. The applied system uses Wang dataset for thepurpose of training and testing the system. And other 100 images that are not fromdataset is also used for testing system. The overall accuracy of the system is over80% for all classes. The system is implemented with MATLAB programminglanguage on window platform."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value": []}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-09-23"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "ChuThinzar.pdf", "filesize": [{"value": "2065 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 2065000.0, "url": {"url": "https://meral.edu.mm/record/4303/files/ChuThinzar.pdf"}, "version_id": "344e2457-0455-4515-a769-45d9a4a9407b"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "University of Computer Studies, Yangon", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Tinzar, Chu"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Thesis"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2019-03"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/2243"}, "item_title": "Content-Based Image Classification and Retrieval using Support Vector Machine", "item_type_id": "21", "owner": "1", "path": ["1597824322519"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004303", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-09-23"}, "publish_date": "2019-09-23", "publish_status": "0", "recid": "4303", "relation": {}, "relation_version_is_last": true, "title": ["Content-Based Image Classification and Retrieval using Support Vector Machine"], "weko_shared_id": -1}