TRIOS - an open source toolbox for training image operators from samples
نویسندگان
چکیده
Image processing is a valuable tool in many areas, including medical image analysis, document processing and bioinformatics. However, designing good image operators requires deep knowledge in both image processing and the area of application, and the designed operator might not be the best possible. Automatic training of image operators allows people with little knowledge in Image Processing to design good (sometimes optimal) image operators by providing pairs of images that contains examples of the input and the output of the desired operator. However, to the best of our knowledge, there is no toolbox that makes the design of such image operators an easier task for non-specialists. In this work, we present TRIOS, an in development research toolbox that contains algorithms to train morphological image operators from samples in an easy and unobtrusive way. Keywords-Mathematical morphology; Image Operators; Supervised learning; Toolbox
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تاریخ انتشار 2012