2D image recognition of partially occluded objects based on adaptive window positioning and dynamic time warping

Abstract

The boundaries of computer vision are e specially challenged by partial occluded object recognition. In this paper, we proposed a new algorithm that used to recognize the partially occluded objects in 2 - D images. Two different cases of occlusion are considered. Firstly, when an object missing so me parts. Secondly, objects are overlapping each other. This approach uses contour of an object. Adaptive Window Positioning (AWP) uses to extract features from a contour. The proposed method uses the orientation field as features of the fragment. Dynamic Time Warping (DTW) works for matching and find the similarity between sub - images. As experiment result, the proposed recognition algorithm works without prior segmentation and robust to identify missing and overlapping objects and it can woks with strength occlusion.