Cocoon Edge Detection based on Self-Adaptive Canny Operator

To overcome the problems of detecting the fake edge as well as losing local edge arising from the detection of the cocoon edge by Canny operator, a new method is proposed in this paper to adaptively determine the high and low thresholds of Canny operator using exponential entropy by the edge gradient feature of the cocoon image. Experimental results show that the edge obtained by using the self-adaptive Canny operator has better connectivity, higher positioning precision and stronger anti-noise capability, and consequently, improved automation of cocoon edge detection, compared with traditional edge detecting methods such as Roberts operator, Sobel operator and Prewitt operator.