Object Edge Detection Using the Magnitude of the Gradient

Edge detection is very important terminology in image processing and for computer vision. Edge detection is in the forefront of image processing for object detection, so it is crucial to have a good understanding of edge detection operators. An improved scheme for contour detection with better performance measure has been proposed in this book with the help of image gradients. A 9x9 Laplacian and Gaussian (LOG) filter has been proposed. The present study has shown that the gradient images obtained by the 9x9 Laplacian and Gaussian (LOG) mask appears to be much clearer with sharp and prominent edges than those obtained through 5x5 Laplacian and Gaussian (LOG) filter and also provides better results than traditional edge detectors. The method has been applied to a number of real life digital images and better performance measure of contour detection has been achieved. Comparative analyses of different edge detection operators in image processing are also presented and discussed. It has been observed that the performance of canny edge detection operator is much better then Sobel, Roberts, Prewitt and Laplacian of Gaussian (LoG) in respect to the image appearance and object boundary.

Autorentext

Dr. Pinaki Pratim AcharjyaProfessore, Dipartimento di CSE, Haldia Institute of Technology, IndiaDr. Jayeeta MajumdarProfessore associato, Dipartimento di CSE, Istituto di tecnologia di Haldia, IndiaDr. Subhankar JoardarProfessore, Dipartimento di CSE, Istituto di tecnologia di Haldia, India