IMAGE RETRIEVAL USING BOTH COLOR AND TEXTURE FEATU
2016-08-23
3 0 0
4.0
Other
Earn points
This PROJECT has a further exploration and study of visual feature extraction. According to the HSV (Hue, Saturation,
Value) color space, the work of color feature extraction is finished, the process is as follows: quantifying the color space
in non-equal intervals, constructing one dimension feature vector and representing the color feature by cumulative
histogram. Similarly, the work of texture feature extraction is obtained by using gray-level co-occurrence matrix (GLCM) or
color co-occurrence matrix (CCM). Through the quantification of HSV color space, we combine color features
and GLCM as well as CCM separately. Depending on the former, image retrieval based on multi-feature fusion is
achieved by using normalized Euclidean distance classifier. Through the image retrieval experiment, indicate that the use
of color features and texture based on CCM has obvious advantage.
Value) color space, the work of color feature extraction is finished, the process is as follows: quantifying the color space
in non-equal intervals, constructing one dimension feature vector and representing the color feature by cumulative
histogram. Similarly, the work of texture feature extraction is obtained by using gray-level co-occurrence matrix (GLCM) or
color co-occurrence matrix (CCM). Through the quantification of HSV color space, we combine color features
and GLCM as well as CCM separately. Depending on the former, image retrieval based on multi-feature fusion is
achieved by using normalized Euclidean distance classifier. Through the image retrieval experiment, indicate that the use
of color features and texture based on CCM has obvious advantage.
matlab
图像
检索
使用
特征
颜色
纹理
Related Source Codes
GMSK Linear Receiver
0
0
no vote
NSGA-II algorithm
0
0
no vote
NSGA-III multi-objective optimization algorithm
0
0
no vote
Compressed sensing example
0
0
no vote
CFAR detector example
0
0
no vote
No comment