Flame edge detection algorithm based on cubic B-spline wavelet transform and Canny algorithm

In order to extract muzzle flame edge information more efficiently, an edge detection algorithm combining cubic B-spline wavelet transform and Canny algorithm was designed. Firstly, the cubic B-spline wavelet function is convolved with the flame image. Secondly, according to the problems existing in Canny algorithm, the gradient template was changed to Scharr operator to add two directions on the basis of the original direction, and the Otsu algorithm with improved image complexity was introduced to select high and low thresholds. Finally, high and low frequency components were obtained by a certain fusion rule, and the final margin image can be obtained by inverse wavelet transform. The experimental results show that the fusion algorithm can accurately locate edge contour, effectively suppress noise very well, and the flame edge detection results are complete and clear. Objective evaluation was better than those results by using single algorithm.