A Novel Shape Descriptor for Object Recognition

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International Journal of Computational and Experimental Science Engineering
Volume:9 Issue:1
A Novel Shape Descriptor for Object Recognition

A Novel Shape Descriptor for Object Recognition

Authors : Elif Ebru ÇAKI, Celal Onur GÖKÇE

Pages : 1-5

Doi:10.22399/ijcesen.1202300

View : 15 | Download : 8

Publication Date : 2023-03-31

Article Type : Research Paper

Abstract :In this study a novel shape descriptor for object recognition is proposed. As a preprocessing stage, Canny edge detection [4] is applied to input images. Output of Canny edge detector, namely edge image, is sampled and various number of points are selected. Chosen points are input to the new shape descriptor. Proposed shape descriptor is composed of deviations from average range and average angle. Shape descriptor is used as a feature extractor output of which is fed to linear classifier. Linear classifier is trained using pseudo-inverse and gradient descent techniques. Full MNIST dataset is used to test the system and results are reported.
Keywords : Shape Descriptor Object Recognition MNIST

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