Cucumber disease recognition based on Global-Local Singular value decomposition

• nonnegative Global-Local Logarithmic singular values is used.
• Global-Local Singular Value vector is constituted.
• Skillfully adjust the dimensionalities of two singular value vectors.
• the key-point vector is constituted as the input of SVM classifier.
• the key-point vector have certain discriminant ability.

Plant leaf based plant disease recognition is becoming an important research topic in the pattern recognition and image processing. Many conventional methods are not effective for plant disease recognition because of the complexity of the disease leaf images. Singular value decomposition (SVD) has shown its advantage over other classical algorithms in terms of clustering accuracy and robustness to the data representation and feature extraction. Nonetheless, there is still considerable room to improve the practical application performance of SVD. To improve the recognition rate of cucumber disease, based on the Gglobal-Local SVD, a recognition method of cucumber disease is proposed. First, the spot image is segmented by the watershed algorithm from each cucumber disease leaf image. Second, each spot image is divided into a few blocks, and then the combining features of Global-Local singular values are extracted and ordered from each block by SVD. Third, the key-point vectors are constructed and their dimensionalities are adjusted to equal to each other. Finally, a SVM classifier is adopted to recognize the class of the unknown disease leaf image. Comparing with the existing cucumber disease recognition methods, the proposed one can extract the key-point features from the spot image whose dimension is significantly lower than that of the original space. Also, it can effectively avoid the key information loss in the usual stochastic feature extraction and selection process. The approach is tested on three kinds of cucumber disease leaf images. In the experiments, the original singular values are replaced by the nonnegative Global-Local Logarithmic singular values. The experimental results show that the proposed method is effective and feasible for the cucumber disease recognition, and has the highest recognition rate and more practical value.