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Image recognition technology is a new plant disease diagnosis. Image segmentation can be isolated lesion and background. The accuracy of its identification has important implications. We propose a new image segmentation algorithm which is based on super-green features and OSTU methods. This segmentation algorithm is good, and easy to implement. It is able to provide good pre-treatment of disease identification results, and improve recognition accuracy. This algorithm was applied in the corn diseases identified study work. The results show that the algorithm has good accuracy. [ABSTRACT FROM PUBLISHER]

Automatic recognization of remote sensing images is significant. In this article, we use optimally pruned extreme learning machine(OP-ELM) as an automatic classifier to achieve recognization of the objects in remote sensing images based on texture features through grey-level co-occurrence matrix method. OP-ELM is based on the original extreme learning machine(ELM) algorithm with additional steps to make it more robust and genetic. For the recognization, several co-occurrence parameters are computed and compared, and then, we used the more obvious features of the texture of the objects in remote sensing images as criterions. To improve the effection of recognization, we bring in threshold filter, erosion filter and so on after the OP-ELM classification. In the experiments, the results for both computational time and accuracy(Kappa coefficients) are compared to the SVM and BP. As the illustration, OP-ELM performs faster than the other algorithm Without losing the accuracy of the premise. [ABSTRACT FROM PUBLISHER]

Environmental assessment of soil has important significance in sustainable utilization for land resource. Entropy weight coefficient method was applied to built evaluation model of soil environment to be effectively reduced the influences of subjective factors in determine the weight. It was analyzed the influence of every factor in the environmental assessment of soil by entropy, and worked out the weight value of evaluation index and obtained the environmental assessment's comprehensive index value. By Compared and analyzed of comprehensive index value, It was obtained that grade of environmental assessment of soil,and the degree of closeness of measured value. It were compared entropy weight coefficient method and the others methods, The results show that entropy weight coefficient method has high accuracy. The above sample analysis demonstrates that the evaluation method is simple and feasible and the evaluation results are in conformity with the actual situation. [ABSTRACT FROM PUBLISHER]