Method for automatically classifying forestry service images

Abstract

The invention relates to a method for automatically classifying forestry service images, comprising the main steps of training and classifying. The step of training is as follows: converting images, calculating the set of key points on a gray-scale image, describing the key points by determining the main direction of the key points and generating eigenvectors, clustering, and producing histograms to express the images. The step of classifying is as follows: expressing the classified images with the histograms, and classifying by a classifier. Therefore, the classification of the forestry service images is finished. The numerous forestry service images collected by the forest rangers are used for constructing a reasonable visual vocabulary book according to the characteristics and the color information of the data of the forestry service images, the forestry service images are divided accurately into seven categories including forest fires, illegal use of forest land, illegal logging, illegal hunting and the like, and the forestry service images of different categories are respectively transferred to the functional management departments to realize the fast, effective and timely management of forest and the information modernization of the management of the forest.

Description

technical field [0001] The invention relates to an automatic forestry business image classification method, which belongs to the technical field of forest resources monitoring and information processing. Background technique [0002] Forestry has huge ecological, economic and social functions, and it is an effective way to deal with the ecological crisis and climate change caused by the development of economic globalization. Therefore, the protection of forest resources and ecology has become an important construction content of governments at all levels. As the backbone of forestry work, forest rangers can transmit forestry field data to the server after being captured by mobile phones. These image data are concentrated on the server and can be quickly classified according to the needs of forestry business, and the classification results are sent to relevant forestry management departments, so that relevant events can be processed in a timely and effective manner. [0003...

AI Technical Summary

Problems solved by technology

[0008] After more than ten years of development, scene image classification has achieved rich results, but it often ignores the color information of the image, and is very sensitive to image scaling.

In particular, the current research on scene image classification is still on some general natural landscape images, and the differences between different categories of images are quite large.

However, the research on automatic classification of forestry business images has not been reported yet.

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