Edge detection based on wavelet analysis with Gaussian filter

In this paper an edge detection algorithm base on wavelet transform with Gaussian filter was proposed. In this algorithm original images are firstly converted into gray images and then each pixel was analyzed using wavelet transform to find the local maximum of the gray gradient of each pixel along the phase angle direction and compared with a given threshold value, through which real edge can be kept and fake ones will be eliminated. In the computation of local maximum, the gray gradients computed in eight directions, which can improve precision of edge detection. After the investigation of influence of filter length, scale and threshold value on the edge detection the proposed algorithm is validated by the comparison with N.L. Fenández- García's Minimean and Minimax methods for 100 real color images. The extraction result is more close to the real image which indicates the algorithm is effective and can be used to extract edges in different research areas.