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Shape Detection using Geometrical Features


Affiliations
1 Dept. of Computer Science & Engineering and I.T, 1Assam Don Bosco University, Guwahati, Assam, India
2 National Institute of Electronics and Information Technology (NIELIT), Kolkata, India
 

In this paper, we have presented an approach for object detection system. This approach is used for detect two-dimensional shapes such as lines, rectangle, square, circle, triangle, polygon, star etc. Proposed technique of shape detection is based on the statistical properties of distribution of points on bitmap image and sub-windowimage of a shape. For recognition, we have considered sub-windowbased features and Nearest Neighbours classifier. By applying these features, we achieve maximum recognition accuracy of 96.7% using 4556 samples.

Keywords

Shape Detection, Feature Extraction, Geometric Features.
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  • Shape Detection using Geometrical Features

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Authors

Shalu Gupta
Dept. of Computer Science & Engineering and I.T, 1Assam Don Bosco University, Guwahati, Assam, India
Y. Jayanta Singh
National Institute of Electronics and Information Technology (NIELIT), Kolkata, India

Abstract


In this paper, we have presented an approach for object detection system. This approach is used for detect two-dimensional shapes such as lines, rectangle, square, circle, triangle, polygon, star etc. Proposed technique of shape detection is based on the statistical properties of distribution of points on bitmap image and sub-windowimage of a shape. For recognition, we have considered sub-windowbased features and Nearest Neighbours classifier. By applying these features, we achieve maximum recognition accuracy of 96.7% using 4556 samples.

Keywords


Shape Detection, Feature Extraction, Geometric Features.

References