A New Variance Operator for Detecting Edges in Images
Yang Chen · 2010
Detecting edges in images is a fundamental and useful technique in image processing. In this paper, we propose a new variance operator for edge detection. The pixel values within a mask are normalized so that they can be treated as probabilities. Then, the variance of the probabilities is calculated. A threshold is chosen for generating the black and white edge image. Morphological operation is applied as post processing for refining the edges. Simulation results show that the proposed method has consistent performance on various sample images, which is competitive with the Sobel, Canny, and entropy operators.