A New Edge Detector in CT Scan Images Using Gradient of Weibull Distribution

CT Scan is based on the x-ray principal: as x-rays pass through the body they are absorbed or attenuated (weakened) at differing levels creating a matrix or profile of x-ray beams of different strength. This x-ray profile is registered on film, thus creating an image. In the case of CT. Image processing uses for detecting for objects of CT images. Edge detection; which is a method of determining the discontinuities gray level images, is a very important initial step in Image processing. Many classical edge detectors have been developed over time. Some of the well-known edge detection operators based on the first derivative of the image are Roberts, Prewitt, Sobel which are traditionally implemented by convolving the image with masks. Also Gaussian distribution has been used to build masks for the first and second derivative. However, this distribution has a limit to only symmetric shape. This paper will use to construct the masks. The Weibull distribution which was more general than Gaussian because it has symmetric and asymmetric shape. The constructed masks are applied to images and we obtained good results. KeywordsEdge detection; Image processing; Weibull Distribution; Gradient; CT scan images. WCSIT 4 (1), 13 -17, 2014 14 Where is first order derivative of ) , ( y x f define as: