We propose an image segmentation algorithm that is based on spatially adaptive color and texture features. The features are first developed independently, and then combined to obtain an overall segmentation. Texture feature estimation requires a finite neighborhood which limits the spatial resolution of texture segmentation, while color segmentation provides accurate and precise edge localizati...

In four studies children were asked to read aloud a passage of randomly ordered common words with and without a coloured sheet of plastic (overlay) placed upon the page. The children's rate of reading increased with the overlay, for some children more than for others. The children were also asked to undertake a test of texture segmentation in which targets consisting of a structured texture had...

Object segmentation is a fundamental task in various computer vision applications. Although used extensively for object recognition, texture has lately been ignored as a feature used for background modelling and object segmentation. The complexity of working with texture descriptors for segmentation in videos is two-fold: the descriptive features cannot be calculated in real time and features e...

The segmentation of textures using features extracted with 2-D moving average (MA) modeling approach is presented in this paper. The 2-D MA model represents a texture as an output of a 2-D nite impulse response (FIR) lter with simple input process. The 2-D MA model is exible, and can be used for modeling both isotropic and anisotropic textures. The maximum-likelihood (ML) estimators of the 2-D ...

We present an image segmentation algorithm that is based on spatially adaptive color and texture features. The proposed algorithm is based on a previously proposed algorithm but introduces a number of new elements. We use a new set of texture features based on a steerable filter decomposition. The steerable filters combined with a new spatial texture segmentation scheme provide a finer and more...

This thesis presents the development of a theoretical framework capable of encompassing the colour and texture information in a robust image descriptor that can be applied to the identification of coherent regions in complex natural images. In the suggested approach, the colour and texture features are extracted explicitly on two independent channels and the main emphasis of this work was place...

In this paper, a novel unsupervised segmentation framework for texture image queries is presented. The proposed framework consists of an unsupervised segmentation method for texture images, and a multi-filter query strategy. By applying the unsupervised segmentation method on each texture image, a set of texture feature parameters for that texture image can be extracted automatically. Based upo...