Trunk texture recognition method based on four-channel convolutional neural network

Abstract

A trunk texture recognition method based on a four-channel convolutional neural network comprises the following steps: S1, collecting a trunk image data set to ensure the integrity of an image; s2, preprocessing the image; and S3, training a multi-classifier by using the four-channel convolutional neural network. According to the invention, richer image feature information can be obtained, features with higher discrimination can be learned automatically, and the classification precision and robustness of the classifier obtained by training are higher.

Description

technical field [0001] The invention belongs to a tree trunk texture recognition method based on a four-channel convolutional neural network, and relates to a convolutional neural network, digital image processing and image classification methods. Background technique [0002] In recent years, with the development of China, people's calls for ecological protection have become higher and higher, and the protection of plant diversity has become more and more important. How to obtain tree information through simple pictures, such as species and growth habits, is one of the important methods to simplify tree species identification, and it is of great significance for protecting plant diversity and strengthening agricultural and forestry information management. [0003] At present, tree identification and classification are mostly done manually. However, there are so many types of trees that it is impossible for any botanist to remember the names of all tree species. For people w...

AI Technical Summary

Problems solved by technology

For example, it is difficult to identify tree species when the flowers and leaves are gone in winter, and the texture of many leaves is relatively delicate, which requires high camera equipment and is difficult to accurately identify

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