A Method for Object Detection in Colored Images using Improved Point Feature Matching: Improved Point Feature Matching for Real-time Object Detection in Colored Images

Abstract

For some of application which involve detection of any object though a digital image, image matching is an essential trait. For detecting a particular object within an image, detection using point feature method is much effective technique. The Point feature matching within an image is done by comparing various correspondence points of object and analyzing the points between cluttered scene image to find a required object of interest in image. In this paper, a modified approach of Point feature matching with novel SURF algorithm is used for extracting the information from image, describing the points, matching object and detecting of object of interest in colored images. The algorithm works on finding correspondence points between a target and reference images and detecting a particular object. Speeded-up robust features (SURF) algorithm is used in this study which can detect objects for unique feature matches with non-repeating patterns. This approach of detection can vigorously find specified objects of interest within an colored image even with cluttered objects in image and provide constriction to other achieving near real time performance. The algorithm can be used for real time detection of object for military weapons guidance.