A Comparative Approach for Standard Shadow Detection Methods

Kavita ., Manoj K Sabnis


False tracking is the biggest problem identified in tracking. The reasons for this is identified as shadow of the object to be tracked which have their shape mapping to the shape of the object.  Dynamic shadow detection is the field in which videos are used. Dynamic shadow detection is found to be more exposed in literature due to the possibility of comparison, frame differentiation, background subtraction. All this not being possible in case of static images as they represent a single frame and are not used to that extent. Taking this as a challenge this paper presents static shadow detection in which the static shadow detection methods are mapped with dynamic images within the domain of image processing.The results so obtained are then authenticated from the user side. Every user may have different views, so as to bring the evaluation at a standard level this qualitative evaluation is quantified so as to be represented in form of tables and graphs for further analysis.

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JianeYao, Zhongfei Zhang,(2004) ”Systematic Static Shadow Detection”, Proceedings of the 17th International Conference on pattern Recognition,1051-4651, IEEE, Computer Society.

Jasmin T Jose, V K Govindan, (2013)"Efficient algorithm for varying area based shadows detection in videos sequences", International Journal of Computer Applications,June,72(16) : 975: 8887.

Kaushik Deb, Animesh Kar, Ashraful Huq Suny,(2014)“Cast Shadow Detection and Removal of Moving Objects from Video Based on HSV Color Space”.

Neha Hail, Somesh Dewangan (2013) “Comparative Study:Detection of Shadow and itsRemoval”, International journal of Engineering Research and Application,ISSN 2248-9622, July-August, l3 (4):2080:2083.

Chia-Jung Chang,Wen –Fong Hu,Jun –Wei Hsiehand Yung-Sheng Chen (2002) “ Shadow Elimination for effective Object detection”,15th IPPR Conference on computer vision, graphics and Image Processing:185:192.

“Hierarchical static shadow Detection methods” US 7,970,168 B1.

Leone ,C Distante, (2006) “Shadow Detection for Moving Objects based on Texture Analysis”, The Journal of Pattern Recognition ,ISSN 0031-3203,pattern recognition 40(2007) Elsevier, September: 1222:1233.

Andrzej Mateka and Michal Strzelecki, (1998) "Texture Analysis methods-review" Technical university of Lodz, institute of electronics, report,Brussels.

Prati Andrea, MikicIvana, Trivedi, Mohan Manubhai, Cucchiara Rita, (2003) “Detecting moving shadows: Algorithm and evaluation” IEEE Transaction On Pattern Analysis And Machine Intelligence, July, 25 (7): 918:923.

Andres Sanin, Conrad Sanderson, Brain C Lovell (2012), “Shadow Detection: A survey andcomparative evaluation of recent methods”,Pattern Recognition, Elsevier ISSN 0031-3203, 45(4):1684:1695.

Habib Ullah, Mohib Ullah, Muhammad Uzair and Fasihur Rehmn, “Comparative study: Theevaluation of shadow detection Methods”, International Journal of video and image processing and network Security:10 (2):1:7.

Andrea Prati, Ivana Mikie, Mohan M Trivedi, Rita Cucchiara,“Detecting Moving shadows: Formulation, Algorithms and Evaluation” Technical Report-Draft Version:1:39.

DOI: https://doi.org/10.23956/ijermt.v6i8.156


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