Automatic object detection and matching based on proposed signature

The traditional approaches to object to detection and classifications only look at local pieces of an image; it is within a sliding window or the regions around an interest point detector. This paper introduces a new idea for automatic object detection based on its own proposed signature. This signature is completely distinct, simple to use, saved in small memory, and it is determined in different lights on objects. Exceedingly, the matching is very fast and more accurate under not clearing constraint. After determination of signatures, the matching process among the inputs object's signature and other saved standard shapes signatures done. This comparison is making among input signatures with other memorized signatures of saved basic standard shapes, like circle, square ellipse rectangle triangle and so on. This proposed method examines 95 different objects and achieved 92.5% of expected right matching.