Implementation of Multilevel Threshold Method for Digital Images Used In Medical Image Processing

These The digital image processing has been applied in several areas, especially where it is necessary to use tools forfeature extraction and to get patterns of the studied images. In an initial stage, the segmentation is used to separate the image in parts that represents a interest object, that may be used in a specific study. There are several methods thatintends to perform such task, but it is difficult to find a method that can easily adapt to different typeof images, that often are very complex or specific. To resolve this problem, this workaims to presents anadaptable segmentation method, that can be applied to different typeof images, providing a better segmentation. The proposed method is based ona model of automatic multilevel thresholding and considers techniques of group histogram quantization, analysis of the histogram slope percentage and calculation of maximum entropy to define the threshold.