分类器特征提取
对应一组图像而言，图像分类应用较为广泛，如何选取特征很关键：FeatureVector := []
* Compute features.
gen_sobel_features (Image, FeatureVector, FeatureVector)
* Downscale the image (image pyramid) and compute features.
zoom_image_factor (Image, Zoomed1, 0.5, 0.5, 'constant')
gen_sobel_features (Zoomed1, FeatureVector, FeatureVector)
* Uncomment lines to use further pyramid levels:
zoom_image_factor (Zoomed1, Zoomed2, 0.5, 0.5, 'constant')
* gen_sobel_features (Zoomed2, FeatureVector, FeatureVector)
* zoom_image_factor (Zoomed2, Zoomed3, 0.5, 0.5, 'constant')
* gen_sobel_features (Zoomed3, FeatureVector, FeatureVector)
* zoom_image_factor (Zoomed3, Zoomed4, 0.5, 0.5, 'constant')
* gen_sobel_features (Zoomed4, FeatureVector, FeatureVector)
FeatureVector := real(FeatureVector)gen_sobel_features如下：
* Coocurrence matrix for 0 deg and 90 deg:
cooc_feature_image (Image, Image, 6, 0, Energy, Correlation, Homogeneity, Contrast)
cooc_feature_image (Image, Image, 6, 90, Energy, Correlation, Homogeneity, Contrast)
* Absolute histogram of edge amplitudes:
sobel_amp (Image, EdgeAmplitude, 'sum_abs', 3)
gray_histo_abs (EdgeAmplitude, EdgeAmplitude, 8, AbsoluteHistoEdgeAmplitude)
* Entropy and anisotropy:
* entropy_gray (Image, Image, Entropy, Anisotropy)
* Absolute histogram of gray values:
* gray_histo_abs (Image, Image, 8, AbsoluteHistoImage)
* Add features to feature vector:
FeaturesExtended :=
FeaturesExtended :=
* FeaturesExtended :=
* FeaturesExtended := 金字塔式的纹理特征求解；
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