Color and Position versus Texture Features for Endoscopic Polyp Detection (original) (raw)
This paper presents a comparison of texture based and color and position based methods for polyp detection in endoscopic video images. Two methods for texture feature extraction that presented good results in previous studies were implemented and their performance is compared against a simple combination of color and position features. Although this more simple approach produces a much higher number of features than the other approaches, a SVM with a RBF kernel is able to deal with this high dimensional input space and it turns out that it outperforms the previous approaches on the experiments performed in a database of 4620 images from endoscopic video.
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