Accurate and efficient shape matching approach using vocabularies of multi-feature space representations

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dc.contributor.author Shehzad Khalid
dc.contributor.author Sadaf Sajjad
dc.contributor.author Sohail Jabbar
dc.contributor.author Hangbae Chang
dc.date.accessioned 2017-12-26T12:01:03Z
dc.date.available 2017-12-26T12:01:03Z
dc.date.issued 2014
dc.identifier.uri http://hdl.handle.net/123456789/5193
dc.description.abstract Selection of compressed, robust and accurate features is the fundamental ingredient of effective contentbased image recognition and retrieval using shape information of objects in the image. In this paper, we present a four-stage system for real-time object recognition and retrieval that employs multiple feature space representation using contour information. In the first stage, we pre-process the shapes to cater for the presence of distortions such as cracks that can significantly distort the contour information of the shape. We then generate multiple feature space representations of shapes to be used later in proposed combination for efficient and accurate retrieval of shapes using a hierarchical indexing structure. To enable real-time image-based shape analysis by enhancing the efficiency and reducing the storage requirement of proposed shape descriptors, we present a quantization approach to generate vocabulary of feature space representation of shapes. These features are then combined in an ensemble for accurate and efficient shape retrieval and recognition in the presence of large shape datasets. The proposed system is evaluated using publicly available shape datasets such as MPEG 7, Swedish leaf and KIMIA 99 datasets. Our approach achieves higher accuracies which are better than state-ofthe- art approaches reported in literature whilst looking at a small subset of shapes in dataset. en_US
dc.language.iso en en_US
dc.publisher Bahria University Islamabad Campus en_US
dc.subject Department of Computer Engineering CE en_US
dc.title Accurate and efficient shape matching approach using vocabularies of multi-feature space representations en_US
dc.type Article en_US


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