A Study on Texture Segmentation Towards Content-based Image Retrieval
نویسنده
چکیده
Extended Abstract: Texture segmentation is an important but challenging task in image analysis or computer vision applications. Among various cues, texture plays a vital role towards object recognition. Recent studies reveal the two popular methods for texture analysis: filter bank methods and Gray level cooccurrence matrices (GLCM). In this work, we have proposed several texture features in the spatial and transform domain as well as some approaches for texture segmentation and applications based on multi-channel filtering technique. Among them, the wavelet intermittency based salient points and wavelet transform-based locally orderless images (WLOIs) are remarkable. The later approach is versatile one, which may combine the filter bank methods with cooccurrence matrices for many applications. Contributions are elaborated below.
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