NDLI: Approach for shadow detection and removal using machine learning techniques

Content Provider	IET Digital Library
Author	Shilpa, Mohankumar Gopalakrishna, Madigondanahalli Thimmaiah Naveena, Chikkaguddaiah
Abstract	In this work, the authors have proposed a method for shadow detection and removal from videos by utilising methods of machine learning. From literature, various algorithms on shadow detection and removal have been accounted with advantages and disadvantages. Here some algorithms have a need for manual alignment and predefined explicit parameters, but fail to give precise outcome in different lighting and ecological surroundings. In this work, the authors propose a three-phase framework. In first stage, key frames are chosen by utilising features based K-means clustering which selects the key frames using features like colour, shape and surface. In second stage, they utilised two-stage segmentation techniques to segment the shadows by marking the region of interest. In the final step, they use threshold based segmentation to remove the shadow in videos. The performance of the proposed method is compared by performance evaluation of all state-of-the-art methods. The proposed strategies are established to achieve superior results in comparison to other state-of-the-art methods.
Starting Page	2998
Ending Page	3005
Page Count	8
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 13, Nov (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/13
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2020.0001
Journal	IET Image Processing
Publisher Date	2020-05-20
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Data Handling Technique Feature Selection Image Recognition Image Segmentation K-means Clustering Algorithm Knowledge Engineering Technique Learning in AI Machine Learning Pattern Clustering Shadow Detection Shadow Removal Two-stage Segmentation Technique Video Signal Processing
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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