  Object recognition is an important task in image processing and computer
vision. This paper presents a perfect method for object recognition with full
boundary detection by combining affine scale invariant feature transform
(ASIFT) and a region merging algorithm. ASIFT is a fully affine invariant
algorithm that means features are invariant to six affine parameters namely
translation (2 parameters), zoom, rotation and two camera axis orientations.
The features are very reliable and give us strong keypoints that can be used
for matching between different images of an object. We trained an object in
several images with different aspects for finding best keypoints of it. Then, a
robust region merging algorithm is used to recognize and detect the object with
full boundary in the other images based on ASIFT keypoints and a similarity
measure for merging regions in the image. Experimental results show that the
presented method is very efficient and powerful to recognize the object and
detect it with high accuracy.
