Training method, recognition method and device of underwater sea urchin image recognition model

Abstract

The invention discloses a training method, a recognition method and a device for an underwater sea urchin image recognition model. The training method comprises the following steps: constructing an underwater sea urchin image recognition model; obtaining an underwater sea urchin image data set; performing multi-scale color restoration on the underwater sea urchin image data set; processing the underwater sea urchin image data set through a dark channel prior method; performing image fusion on the underwater sea urchin image data set subjected to multi-scale color restoration and the underwater sea urchin image data set processed by a dark channel prior method; sharpening the fused image data set to obtain a training image data set; and training the underwater sea urchin image recognition model by using the training image data set. According to the method, the image is subjected to multi-scale color restoration and dark channel prior processing, and image fusion and sharpening processing are carried out based on the point sharpness weight method, so that the image quality is improved, and the accuracy of subsequent sea urchin target detection is improved.

Description

technical field [0001] The invention belongs to the field of underwater image target detection, and more particularly, relates to a training method, a recognition method and a device for an underwater sea urchin image recognition model. Background technique [0002] With the continuous development of artificial intelligence technology, artificial intelligence technology has also been applied to the automatic fishing of underwater sea urchins. One of the most important parts of automatic underwater sea urchin fishing is underwater sea urchin target detection. Due to the complex underwater environment and low light intensity, underwater sea urchin images usually have a series of problems such as blur, low contrast and chromatic aberration. Common target recognition detection methods, such as SSD, YOLO, etc., have good detection accuracy in terrestrial environments, but cannot cope well with complex underwater environments. SUMMARY OF THE INVENTION [0003] The present inven...

AI Technical Summary

Problems solved by technology

Therefore, there is a need for a training method, recognition method and device for an underwater sea urchin image recognition model to solve a series of problems in underwater sea urchin detection, such as underwater sea urchin images usually appear blurred, low contrast and chromatic aberration, etc.

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