With the advent of computer technology, more and more images will be presented in an electronic form. Hence, we will need more advanced methods to deal with these images as they are becoming an indispensable part of our daily life. Plenty of knowledge can be hidden in images, however very little literature discusses knowledge discovery on them. Moreover, most existing data mining algorithms have been designed for mining categorical or numerical data, and are not suited for image. On the other hand, most image processing methods were focused on processing, not analyzing the image, thus, few of them can be used to mine the image. In this book, we present a framework based on decision trees for both of image mining and image processing. It can automatically mine useful information of the given images and learn the effect within. The learned effects can even be applied to process other images. Thus, we can create an image processing model with a desired effect by using variety of training images. The method described in this book is especially suitable for everyone who wants to mine knowledge from the image and for people who wish to create their personalized image processing model.
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