Abstract
Shadow removal has evolved as a pre-processing step for various computer vision tasks. Several studies have been carried out over the past two decades to eliminate shadows from videos and images. Accurate shadow detection is an open problem because it is often considered difficult to interpret whether the darkness of a surface is contributed by a shadow incident on it or not. This paper introduces a color-model based technique to remove shadows from images. We formulate shadow removal as an optimization problem that minimizes the dissimilarities between a shadow area and its non-shadow counterpart. To achieve this, we map each shadow region to a set of non-shadow pixels, and compute an anchor value from the non-shadow pixels. The shadow region is then modified using a factor computed from the anchor value using particle swarm optimization. We demonstrate the efficiency of our technique on indoor shadows, outdoor shadows, soft shadows, and document shadows, both qualitatively and quantitatively.
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Saritha Murali is currently pursuing her Ph.D. degree in image processing at the Department of Computer Science and Engineering, National Institute of Technology Calicut, India. She holds her B.Tech. degree in computer science and engineering from Kannur University, India, and M.Tech. degree in computer science (information security) from the National Institute of Technology Calicut, India. Her research interests are in the areas of computer vision and image processing. She has a few research publications to her credit.
V. K. Govindan is an Emeritus Professor in computer science and engineering. He served in the Department of Computer Science and Engineering of National Institute of Technology Calicut from 1982 to 2015. He has also worked as professor in computer science and engineering at the Indian Institute of Information Technology, Kottayam. He completed his bachelor and master degrees in electrical engineering in the National Institute of Technology Calicut, and obtained his Ph.D. degree in the area of character recognition from the Indian Institute of Science, Bangalore. He has more than 40 years of teaching and research experience and has served as head of the Department of Computer Science and Engineering, and academic dean at the National Institute of Technology Calicut. His research interests include image processing, pattern recognition, machine learning, and operating systems. He has more than 180 research publications, completed several sponsored research projects, authored 20 books, produced 15 Ph.D.s, and is currently guiding two Ph.D. scholars.
Saidalavi Kalady is an associate professor in the Department of Computer Science and Engineering at the National Institute of Technology Calicut. He received his M.E. degree in computer science from the Indian Institute of Science, Bangalore, and Ph.D. degree in agent-based systems from the National Institute of Technology Calicut. He has served as head of the Department of Computer Science and Engineering at the National Institute of Technology Calicut. His research interests include computational intelligence and operating systems.
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Murali, S., Govindan, V.K. & Kalady, S. Single image shadow removal by optimization using non-shadow anchor values. Comp. Visual Media 5, 311–324 (2019). https://doi.org/10.1007/s41095-019-0148-x
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DOI: https://doi.org/10.1007/s41095-019-0148-x