Shadow Detection and Its Removal from Images Using Advance Strong Edge Detection Method (ASED)
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 6
Abstract
Shadow causes dilemma during the recognition of objects from images in different computer vision applications, so it is a very critical job to confiscate shadow from images that’s why in this paper a new method for shadow removal based on Advance Shadow Edge Detection (ASED) method is projected. First of all an image is converted into the gray-scale image then this resulted image produces the edge patch candidates and after applying feature extraction and edge classifier technique on the resulted edge patch candidates strong shadow edges are generated. Additionally spatial smoothing is used for get improved shadow recognition results at the end Gaussian filter is applied for shadow elimination task. After Shadow removal some image parameters (Mean Square Error, Maximum Squared Error and ratio of squared norms) outcome of both earlier Patch based Shadow Edge Detection Method and projected ASED method are calculated and compared with each other. The consequences demonstrate that the projected ASED method is better than the previous Patch Based Shadow Edge Detection method. Mean square error and Maximum squared error are less than earlier method which shows the shadow detection and removal are more efficiently performed through our Advance Shadow Edge Detection (ASED) method.
Authors and Affiliations
Anshul Bhatia, Jyoti Yadav, Eisha Jain, Sangeeta
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