Leaf recognition using contour based edge detection and SIFT algorithm

The paper presents two advanced methods for comparative study in the field of computer vision. The first method involves the implementation of the Scalar Invariant Fourier Transform (SIFT) algorithm for the leaf recognition based on the key descriptors value. The second method involves the contour-based corner detection and classification which is done with the help of Mean Projection algorithm. The advantage of this system over the other Curvature Scale Space (CSS) systems is that there are fewer false-positive (FP) and false-negative (FN) points compared with recent standard corner detection techniques. The performance analysis of both the algorithm was done on the flavia database.