SHAPE MATCHING AND OBJECT RECOGNITION USING COMMON BASE TRIANGLE AREA
Authors:
Ms.A.Venkata Lakshmi, Mr.K.Vamshi, Mr. K. Nandu, Mr. S.Dileep
Page No: 259-267
Abstract:
ABSTRACT-Shape matching and object recognition are essential areas of study in computer vision, with applications spanning robotics, medical imaging, augmented reality, and security systems. One of the key challenges in these domains is developing efficient and reliable algorithms that can accurately recognize and match objects despite variations in scale, rotation, and orientation. This project explores a novel approach to shape matching and object recognition using a geometric feature known as the common base triangle area. The method focuses on decomposing complex shapes into simple,manageable geometric components, making the matching process both efficient and scalable.In this approach, we extract key triangular structures from the contours of objects and calculate the areas of triangles that share common bases. This technique leverages the principle that objects with similar shapes will have a consistent relationship between their base triangles, even if the objects are distorted or rotated. By comparing these geometric features, the algorithm can match shapes and recognize objects with high precision. The approach is robust to transformations like translation, scaling, and rotation, making it ideal for real-world applications where objects may not appear in a standardized orientation. The proposed method is evaluated on various datasets, comparing its performance against traditional shape matching techniques. The results demonstrate the algorithm’s ability to achieve high accuracy in object recognition tasks, while also providing computational efficiency. In addition, the method’s scalability makes it suitable for large-scale object recognition systems, such as automated image classification or real-time object tracking in video surveillance.
Description:
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Volume & Issue
Volume-13,ISSUE-12
Keywords
Keywords: Recognition, Detection, CBTA