Same family object matching is widely used in many applications such as object detection and tracking. In this article, we present an efficient way to search for objects in the same family. The proposed method is in fact an improved version of the BBS method, which in addition to having the positive features of this method such as resistance to background crowds, obstruction, scaling, change of angle and deformation, due to use of the characteristics of Haar wavelet, it is resistant to changes in light intensity and gives more accuracy in matching operation. The nature of the proposed method is based on the number of pairs of points that have the best matching, and has unique features that, by separating the features extracted from the image texture, make the matching operation be more accurate and less sensitive to changes in light intensity. Given the many difficulties in finding correspondence, we have proposed a method that overcomes many challenges. In the evaluation phase, by challenging the act of matching in a set of standard images of household objects, including the BBS database and other sports images, animals, objects, film scenes, and MRI images, the test results of the proposed method outperform against other methods.