{"id":{"repo_id":"malta","oai_identifier":"oai:www.um.edu.mt:123456789/92011"},"canonical_url":"https://search.dev.ndltd.org/etd/malta/oai:www.um.edu.mt:123456789/92011","repository":{"repo_id":"malta","name":"University of Malta","base_url":"https://www.um.edu.mt/library/oar/oai/request"},"display":{"title":"Sketch similarity searching","abstract":"Nowadays, a number of application fields, such as military, bio-medicine, education and the World Wide Web (WWW), use a large volume of image data. This necessity for better image searching techniques has instigated researchers to study new technologies that could be the pinnacle of next generation image retrieval systems. Current technologies allow the user to search only by text content. However, this searching environment contrasts the way humans perceive an image. In this project, we create a sketch search engine that facilitates users' actions in finding similar images based on various cues, such as colour, shape, hue, brightness and other relevant criteria, which have been inputted interactively as a sketch. The system framework represents an image by a set of regions, which more or less correspond to objects, characterised by colour, shape, location and area. The system segments an image into regions in the quest of extracting features from each region. Sketch searching is based on finding similar extracted features in images, and the images with the highest ranking are displayed to the user. To evaluate the system, a number of users with different backgrounds will be asked to rate for the results retrieved, given a sketch.","abstract_html":"Nowadays, a number of application fields, such as military, bio-medicine, education and the World Wide Web (WWW), use a large volume of image data. This necessity for better image searching techniques has instigated researchers to study new technologies that could be the pinnacle of next generation image retrieval systems. Current technologies allow the user to search only by text content. However, this searching environment contrasts the way humans perceive an image. In this project, we create a sketch search engine that facilitates users' actions in finding similar images based on various cues, such as colour, shape, hue, brightness and other relevant criteria, which have been inputted interactively as a sketch. The system framework represents an image by a set of regions, which more or less correspond to objects, characterised by colour, shape, location and area. The system segments an image into regions in the quest of extracting features from each region. Sketch searching is based on finding similar extracted features in images, and the images with the highest ranking are displayed to the user. To evaluate the system, a number of users with different backgrounds will be asked to rate for the results retrieved, given a sketch.","abstract_has_math":false,"creators":[],"institution":"University of Malta","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2007,"date_issued":"2007","date_published":"2007","updated_at":"2026-07-27T20:12:39Z","subjects":["Pattern recognition systems","Computer vision","Image segmentation"],"languages":["en"],"rights":["info:eu-repo/semantics/restrictedAccess"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://www.um.edu.mt/library/oar/handle/123456789/92011","outbound_label":"Repository record","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-03-23T07:45:59Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-03-23T07:45:59Z"]},{"key":"dc:date.issued","label":"Date","values":["2007"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Faculty of Information and Communication Technology. 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IT (Hons)(Melit.)"]},{"key":"dc:description.abstract","label":"Abstract","values":["Nowadays, a number of application fields, such as military, bio-medicine, education and the World Wide Web (WWW), use a large volume of image data. This necessity for better image searching techniques has instigated researchers to study new technologies that could be the pinnacle of next generation image retrieval systems. Current technologies allow the user to search only by text content. However, this searching environment contrasts the way humans perceive an image. In this project, we create a sketch search engine that facilitates users' actions in finding similar images based on various cues, such as colour, shape, hue, brightness and other relevant criteria, which have been inputted interactively as a sketch. The system framework represents an image by a set of regions, which more or less correspond to objects, characterised by colour, shape, location and area. The system segments an image into regions in the quest of extracting features from each region. Sketch searching is based on finding similar extracted features in images, and the images with the highest ranking are displayed to the user. To evaluate the system, a number of users with different backgrounds will be asked to rate for the results retrieved, given a sketch."]},{"key":"dc:title","label":"Title","values":["Sketch similarity searching"]}]}],"canonical_facts":{"dc:date.accessioned":["2022-03-23T07:45:59Z"],"dc:date.available":["2022-03-23T07:45:59Z"],"dc:date.issued":["2007"],"dc:description":["B.Sc. IT (Hons)(Melit.)"],"dc:description.abstract":["Nowadays, a number of application fields, such as military, bio-medicine, education and the World Wide Web (WWW), use a large volume of image data. This necessity for better image searching techniques has instigated researchers to study new technologies that could be the pinnacle of next generation image retrieval systems. Current technologies allow the user to search only by text content. However, this searching environment contrasts the way humans perceive an image. In this project, we create a sketch search engine that facilitates users' actions in finding similar images based on various cues, such as colour, shape, hue, brightness and other relevant criteria, which have been inputted interactively as a sketch. The system framework represents an image by a set of regions, which more or less correspond to objects, characterised by colour, shape, location and area. The system segments an image into regions in the quest of extracting features from each region. Sketch searching is based on finding similar extracted features in images, and the images with the highest ranking are displayed to the user. 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