Abstract
This paper describes a complementary mechanism that attempts to represent the Interest points (key points)[7][9][10] by a few of the intrinsic parameters in a rotation, scale and translation invariant manner. The parameter for this mechanism of finding interest point is that, the feature points or interest points[7][9][10] correspondences when the shapes of interest are each defined by a single, closed contour and the binary shape we obtained through segmentation represents some realworld object, which was sampled and binarized, and it is that object’s identification that we want to estimate. That means by joining those key points, an image can be extracted. Corner is so special since it is the intersection of two edges; it represents a point in which the directions of these two edges change. Hence, the gradient of the image (in both directions) have a high variation, which can be used to detect it.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
