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3.2.2 The calculation principle and method of texture
feature value
The principle on extraction of texture feature image is that sub
image’s formed by each small window is firstly used to obtain
texture features value by calculating sub-image gray level co
occurrence matrix and the texture feature value denoting this
window is evaluated to the window central point. This has
completed the texture features computation of the first sub
image. Then the window is moved a pixel and forms another
small window image. Next, the author compute texture features
value of new sub-image repeatedly which is evaluated to the
central point of this window. In turn, whole image will form a
texture feature value matrix composed by the texture feature
value which is transformed to the texture feature image.
Figure 4 is the principal of texture feature calculation with the
5x5 sliding window as an example.
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Figure 4. The principle of texture feature calculation
(based on 5x5window)
3.2.3 The procedure and result of texture feature images
of the original image
According to the theory and study, we developed the program
of texture feature extraction by means of VC++. The function
of this procedure is to have a texture analysis and output texture
analysis for input sensing image. The interface of extract
texture feature image is figure 5.
Figure 6. Texture feature image of contrast
Figure 7. Texture feature image of correlation
Figure 8. Texture feature image of entropy
Figure 5. The interface of extract texture feature image
The function of this procedure is clear with simple operation
and strong specialization. We obtain the texture characteristic
images through the procedure.
The texture feature images are obtained through 5 X 5 and 7 X 7 Figure 9. Texture feature image of second moment
sliding windows computing the texture feature value all over
the images. There are as follows:
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