내용기반 의료 세균화상 검색 시스템의 설계 및 구현
Abstract : In this study, we design and implement a content-based medical microbial image retrieval system which can make use of accurate decision on colony as well as efficient education for new technician. For this, we first propose a color feature extraction method, which is able to extract color feature vectors of visual contents from a given microbial image based on especially anaerobic bacteria image using HSV color model. In addition, for better retrieval performance based on large microbial databases, we present an integrated indexing technique that combines with B+-tree for indexing simple attributes such as badge, specimen, department, and microbial name, inverted file structure for text medical keywords acquired from description information, and SBF(Scan-Based Filtering) method for high dimensional color feature vectors. Finally, we expect to decrease rapidly learning time for elementary technicians by well organizing knowledge of clinical fields through proposed system. keyword : Medical Microbial Image, Content-based Retrieval System(CRS), Color Feature Vector
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