RECOGNIZING OBJECT VISUALLY BY USING IMAGE MINING APPROACH

Abstract

Object recognition is a central problem in computer vision research. Most object recognition systems have taken one of two approaches, using either local or global features exclusively. Object recognition, detection and tracking in real time is a necessary task in computer vision. The most objective of this review is to present an overview of the approaches used and also the challenges involved. In this paper we concentrate on different object detection methods, tracking and recognition methods are discuss. Recognition of objects in video can significant benefits to information retrieval including automatic annotation and queries based and content base on the object characteristics recognition of object from Image and video is difficult task and therefore The Speeded Up Robust Features (SURF) descriptor used for recognition produced a reliable performance with regard to change in illumination, scale and rotation of the test images used.. It approximates or even outperforms previously proposed schemes with respect to distinctiveness, repeatability, and robustness, yet can be computed and compared much faster