In a blurred image, the difference of gray level between adhesion pixels and the pixels of background image is small, so it is difficult to accurately segment. Traditional methods for segmenting fuzzy image with adhesion pixels assume that the image is large, and then the computational complexity dramatically expands, which reduces the accuracy of segmentation. In order to solve this problem, t...

“Urban Pixels” are wireless, solar-powered lighting units for cities that blur the boundary between digital display technology and traditional urban lighting. By combining a renewable energy source with RF communication it is possible to achieve a self-sustaining, distributed display network that can be attached to any building surface and reconfigured with ease. Depending on their configuratio...

In the previous chapter, an integrated approach for texture classification using ILCLBP-T is proposed. In continuation to that, the present chapter derived a new co-occurrence matrix based on textons and texture orientation for rotation invariant texture classification of 2D images. The new co-occurrence matrix is called as Texton and Texture Orientation Co-occurrence Matrix (T&TO-CM). The Co-o...

In this paper a comparative study has been made regarding certain methods of image processing by the texture characteristic, to find the optimum method for detecting color texture. The study is based on the experiments. There are two main points: the quality of the detection and the response time. For the experiments have been used the co-occurrence matrix and the iso-segments matrix of the gra...

An image can be compressed if, and only if, its pixels are correlated. This is mentioned many times in Chapter 4, as well as the fact that any image compression method results in decorrelating the pixels. As a result, any transformation that decorrelates values can be the basis for an image compression method. Several such transformations are described in Section 4.4. The topic of this document...