edge histogram matlab
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Hi, I am Krishna. I would like to get details on edge histogram Matlab. I need help on ......etc
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The histogram is the most commonly used feature to represent the overall composition of an image. It is invariant to translation and rotation of the images and normalising the histogram leads to the invariance of the scale. By exploiting the above properties, the histogram is considered very useful for indexing and retrieving images. The edge of the image is considered an important feature to represent the content of the image. It is known that human eyes are sensitive to the characteristics of the edges for the perception of the image. In MPEG-7, there is a descriptor for the distribution of edges in the image. This proposed edge histogram descriptor for MPEG-7 consists only of the local edge distribution in the image. That is, since it is important to keep the histogram size as small as possible for efficient storage of metadata, the normative edge histogram for MPEG-7 is designed to contain only the local edge distribution with 80 cubes. These 80 histogram chambers are the only standardized semantics for the MPEG-7 edge histogram descriptor. However, with local histogram containers only, it is not sufficient to represent the overall characteristics of the edge distribution. Keep in mind that to improve recovery performance, we also need a global distribution of the edges. In this work, we generate the semi-global and global border histograms of the local histogram containers. The global, semi-global and local histogram compartments are then used to evaluate the similarity between the images.

Texture and color are by far the most important and simple functions that are most intuitive to describe objects or images. MPEG-7 has three main descriptors related to texture. Two of them are related to Homogeneous Texture Descriptor, while another is the Edge Histogram Descriptor (EHD).
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