The image Recognition system is a vital problem in the field of computer vision because it must be precise, successful in the desired goal, strong, healthy, and self-loading. The following are the most critical essential phases in image alignment/registration: feature matching, feature detection, derivation of transformation function based on related features in pictures, and reconstruction of images based on generated transformation function. In many applications, the goal of computer vision is to create an ideal and accurate image, which is dependent on optimal feature matching and detection. This paper's inquiry summarizes the similarity among five alternative approaches for robust features/interest points (or landmarks) detector and picture identification. This research also focuses on the extraction of unique features from photos that may be utilized to conduct effective matching of diverse perspectives of the images/objects/scenes.