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Books > Professional & Technical > Technology: general issues
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Feature Extraction and Classification Methods of Texture Images (Paperback)
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Discovery Miles 13 540
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Feature Extraction and Classification Methods of Texture Images (Paperback)
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In texture classification the goal is to assign an unknown sample
texture image to one of a set of known texture classes.Important
applications include industrial and bio medical surface inspection,
for example for defects and disease, ground classification and
segmentation of satellite or aerial imagery, segmentation of
textured regions in document analysis, and content-based access to
image databases. However, despite many potential areas of
application for texture analysis in industry there is only a
limited number of successful examples. A major problem is that
textures in the real world are often not uniform, due to changes in
orientation, scale or other visual appearance. In addition, the
degree of computational complexity of many of the proposed texture
measures is very high.A wide variety of techniques for describing
image texture have been proposed in literature. This work is an
analysis of texture image classification in different classifier
under two different features called wavelet and statistical. The
result shows that image classification with wavelet feature and
feed forward neural network gives better result.
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