Seminar

Detecting edges are an important pre-processing step in image analysis. Best results of image analysis extremely depend on edge detection. Edge detectors are intended to detect and localize the boundaries or silhouettes of objects appearing in images. Up to now many edge detection methods have been developed. But it may have some weaknesses in correct detection of the scope of complications for aerial images or medical images, because of the high variation rate in these images. In image processing tasks, there are various sources of ambiguity and uncertainty to be considered when performing the processing. Images captured situations are not always ideal or stable; this is one of examples of uncertainty regarding the measured pixel values, Also which in some cases is related to the spatial position of an image object or technical limitations. This work introduces a verification framework to detect edges based on interval techniques using measuring diversity of pixel’s intensity and randomness of intensity distribution within the framework of information theory.