Biological image identification system based on telecentric camera matrix and identification method thereof

Abstract

The invention discloses a biological image identification system based on a telecentric camera matrix. The system comprises a camera matrix used for collecting a plurality of original images of a plurality of high-precision local view fields of a detected organism; an image splicing module which is used for registering and splicing a plurality of original images of the high-precision local view field into a spliced image of the high-precision global view field; and a species analysis module which is used for analyzing the spliced image and obtaining a biological species classification prediction conclusion. The invention further discloses a biological image identification method based on the telecentric camera matrix. Compared with the prior art, the system provided by the invention can give consideration to the imaging precision and the imaging range of the detected organism, greatly reduces equipment cost and equipment assembly difficulty, and is convenient to operate. According to the method provided by the invention, automatic identification is realized by steps of image acquisition, registration, splicing feature extraction, analysis and prediction and a mode of identifying the species of the detected organism, and the method has advantages of high identification efficiency, high accuracy, labor cost saving and the like.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a method for identifying biological species through images. Background technique [0002] It is a common method in biological taxonomy to judge the genus and species of a creature by its appearance, physiological characteristics, etc. significance. For a long time, the identification of biological species has faced difficulties such as heavy identification workload, high professional requirements, and high misjudgment rate. In recent years, with the rapid development of technologies in various fields, in order to improve the efficiency of classification and identification of biological species, more and more identification personnel consider combining image processing technology with machine learning methods to realize automatic identification of biological species. [0003] Combining image processing technology and machine learning automatic identification method of b...

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Problems solved by technology

[0005] When the method of combining the above-mentioned image processing technology and machine learning to realize the automatic identification of biological species is applied in practice, it will face the contradiction between image resolution, image recording range and image processing method: on the one hand, for as many as possible To obtain the biological traits of the tested organisms in a detailed and clear manner, a sufficiently high image resolution should be ensured as much as possible; but on the other hand, the identification of biological species often requires a global image of the tested organisms to fully observe the biological characteristics of the tested organisms. Therefore, a sufficiently large image recording range should be ensured as much as possible, and the lens field of view should capture the entire outline of the inspected organism as much as possible; however, due to the incompatibility of high precision and wide range, if a high enough High image resolution and a large enough image capture range not only have strict requirements on the shooting equipment, but also have high requirements on the data processing capability of the image processor, which greatly increases the cost of the equipment and its realization. difficulty

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