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Title: Shadow detection using chromaticity and entropy in colour image

Authors: Ki-Hong Park; Jae-Ho Kim; Yoon-Ho Kim

Addresses: Division of Convergence Computer and Media, 88 Doanbuk-ro, Seo-gu, Daejeon, 35349, Korea ' Division of Convergence Computer and Media, 88 Doanbuk-ro, Seo-gu, Daejeon, 35349, Korea ' Division of Convergence Computer and Media, 88 Doanbuk-ro, Seo-gu, Daejeon, 35349, Korea

Abstract: Shadows in an image often bring a significant problem which can cause unintended negative outcome, so how to detect shadow is an important issue of computer vision tasks. This paper proposed a method to detect shadows from real images. Due to shadows in image have a dark pixel value, shadow candidates are defined. Shadow candidates have been estimated and detected by chromaticity of colour image and threshold image using entropy. Some experiments are conducted so as to verify the proposed method, and results show that the proposed method can detect shadows in colour image.

Keywords: shadow detection; shadow candidates; chromaticity; entropy; single image; minimum cross entropy; maximum entropy; colour distribution; colour model; colour histogram.

DOI: 10.1504/IJITM.2018.089454

International Journal of Information Technology and Management, 2018 Vol.17 No.1/2, pp.44 - 50

Available online: 18 Jan 2018 *

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