Chúng ta có thể xem xét quá trình này colorization một quy tắc bổ sung trực tiếp mà là dựa trên độ sáng điểm ảnh cạnh phát hiện. Thật vậy, chúng tôi đã được thử nghiệm DFC trên tất cả các trường hợp bình thường của cơ sở dữ liệu, không ai trong số họ cho thấy cấu trúc bề ngoài với màu trắng hoặc màu xanh lá cây. | Region Identification Based on Fuzzy Logic 291 c Figure continued density type . We can consider this colorization process an additional rule which is based directly on the detected edge pixel brightness. Indeed we tested DFC on all the normal cases of the database none of them revealed specious structures with white or green colors. We are not claiming that the colorization scheme can be used to classify mammograms but we can use it as one associative rule for mining abnormal mammograms. This issue is our current research program in which we are trying to construct a data mining technique based on association rules extracted from our DFC method for categorizing mammograms. We are also intending for the purpose of mammogram categorization to use other measures besides our DFC association rules like the brightness mean variance skewness and kurtosis for the DFC segmented image. These measures have been reported to have some success in identifying abnormal mammograms 32 . Moreover we experimented with all the edge detection techniques used in Table and proved that no single method can be as effective as our current DFC method 33 . Figure illustrates some comparisons for the stellate cancer image of this article. Table Traditional mammography techniques. Mammography method Reference Gray-level thresholding 23 Comparing left and right breasts 24 Compass filters 25 Laplacian transform 11 Gaussian filters 12 Texture and fractal texture model 17 19 A space scale approach 26 Wavelet techniques 27 Mathematical morphology 28 Median filtering 29 Box-rim method 30 292 Recognizing ROIs in Medical Images c d e f Figure Results of other traditional edge detection techniques. a The kirsch edge detection technique b the Laplacian edge detection technique c Sobel edge detection with contrast enhancement d Prewitt edge detection with contrast enhancement e Cafforio edge detection with inner window 3 and outer window 21 f Canny edge detection Ỗ g .
