Humancentered Contentbased Image Retrieval Cbir Egon L Van Den Broek by Egon L. Van Den Broek 9789090197302, 9090197303 instant download after payment.

Digital media are rapidly replacing their analog counterparts. This development is accompanied by (i) the increasing amount of images present on the Internet, (ii) the availability of the Internet for an increasing number of people, (iii) a decline in digital storage costs, and (iv) the developments in personal digital video/photo camera's. In anticipation of these developments, the fields of computer vision (CV) and content-based image retrieval (CBIR) evolved rapidly. Driven by a technology push, a range of CV/CBIR techniques were developed. However, seldom the user and his characteristics were taken into account and subsequently, limitations of mere technical solutions became apparent. To enable a full analysis of image content (e.g., through object recognition), color and texture analysis has to be done as well as segmentation and shape extraction, to facilitate shape matching. Since each of these topics is essential for CV/CBIR, each of them is discussed, before combining them. A unique color space segmentation, driven by experimental data concerning the 11 color categories, known to be used by humans since half a century. This color space segmentation can function as a highly efficient, human-based, color quantization scheme. On top, a new, parallel-sequential texture analysis approach and a proposal to mimic human texture classification is proposed. Using both elements, a coarse image segmentation was conducted, the first phase of shape extraction. Next, the exact shapes were extracted from such coarse segments by pixelwise classification, followed by smoothing operators. Taken together, a human-based CBIR system has been developed to extract image material.