K-최근방 이웃 방법을 사용한 장면 분류 시스템의 문턱값 접근을 통한 실제 환경에서의 성능 향상 방법Improving K-NN based scene classification system in a practical situation with threshold method

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An Input image is blocked into several blocks and features are extracted from these blocks. Blocks are classified by K-NN classifier using training data with predefined labels, and the most frequently selected block label becomes the label of the image. K-NN based scene classification system is not perfect in a practical situation because there are lots of ambiguous images which even a man cannot tell (indoor from outdoor), (city from landscape), (sunset from mountain&forest), (forest from mountain). Thresholding approach is added to explicitly say that ambiguity exists, and this image has ambiguous label. This increases performance and completeness of previous K-NN based scene classification system.
Publisher
대한전자공학회
Issue Date
2010-06
Language
KOR
Citation

대한전자공학회 하계종합학술대회 , v.33, no.1, pp.148 - 151

URI
http://hdl.handle.net/10203/169819
Appears in Collection
EE-Conference Papers(학술회의논문)
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