NDLI: Evaluation of shadow features

Content Provider	IET Digital Library
Author	Qu, Liangqiong Tian, Jiandong Fan, Huijie Li, Wentao Tang, Yandong
Abstract	Shadow features such as colour ratio, texture, and chromaticity have proved to be quite effective in shadow detection. Many shadow detection methods have been proposed on the basis of different features. However, previous works for shadow detection mainly focus on designing an effective classifier for existing shadow features, but pay less attention on the analysis of shadow features themselves. The majority of studies simply report the final shadow detection results rather than make an evaluation on each feature. Readers often do not know which features are more effective or whether these shadow features are complementary. The following problems are still unsolved: the robustness of each feature, which feature plays the most important role in a detection method, and what is the best performance that current features can reach. The purpose of this study is to answer these questions, and the authors hope that this study can offer guidance for future shadow detection algorithms via the evaluation of frequently used shadow features. Several useful and interesting conclusions are obtained after conducting extensive comparison experiments on a large dataset.
Starting Page	95
Ending Page	103
Page Count	9
ISSN	17519632
Volume Number	12
e-ISSN	17519640
Issue Number	Issue 1, Feb (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/12/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2017.0159
Journal	IET Computer Vision
Publisher Date	2017-08-16
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Chromaticity Colour Ratio Computer Vision And Image Processing Technique Image Classification Image Colour Analysis Image Recognition Image Texture Object Detection Shadow Detection Method Shadow Feature
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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