Deep-sea fish image classification and recognition method

Abstract

The invention discloses a deep-sea fish image classification and recognition method, and the method is characterized in that the method comprises the following steps: 1, building a fish state multi-source information database according to the fin position information amount, fish size information amount, fish tail shape information amount and body color information amount of deep-sea fishes, and dividing the state similarity of the fishes into 0-1; 2, establishing a three-layer neural network based on a BP algorithm; and 3, setting various parameters on the basis of the neural network tool, and training and verifying the neural network. According to the invention, four types of information scoring rules for fish type state evaluation are respectively formulated; a neural network is adoptedas an evaluation algorithm in combination with scoring of the four types of information; the comprehensive score is used as the basis of fish classification, various types of data and parameters areintegrated, the category of deep-sea fishes is comprehensively and accurately evaluated, a scientific basis is provided for deep-sea fish classification, deep-sea fish resources can be effectively developed and utilized, and the strategic significance of long-term development is achieved.

Description

technical field [0001] The invention relates to the technical field of power grids, in particular to a deep-sea fish image classification and recognition method. Background technique [0002] my country is one of the world's largest marine countries, with a sea area of ​​more than 3 million square kilometers. In the vast sea area of ​​our country, there are extremely rich biological resources. According to statistics, there are 20,278 species of marine biological resources in our country, of which there are more than 3,000 fish. species, accounting for about 20% of the world's fish species, but the development and utilization of marine resources in my country is relatively low, and the overall level of marine economic development is not high; [0003] Fish identification is the first step in the detection of marine fish resources and an important basis for the development and utilization of marine resources. However, due to the different shapes and sizes of deep-sea fish, the...

AI Technical Summary

Problems solved by technology

[0002] my country is one of the world's largest marine countries, with a sea area of ​​more than 3 million square kilometers. In the vast sea area of ​​our country, there are extremely rich biological resources. According to statistics, there are 20,278 species of marine biological resources in our country, of which there are more than 3,000 fish. species, accounting for about 20% of the world's fish species, but the development and utilization of marine resources in my country is relatively low, and the overall level of marine economic development is not high;

[0003] Fish identification is the first step in the detection of marine fish resources and an important basis for the development and utilization of marine resources. However, due to the different shapes and sizes of deep-sea fish, the task complexity is higher than other identification tasks. There are many, and different species of the same fish usually have similar shapes, sizes and texture colors, which further increases the difficulty of fish identification. Therefore, research on deep-sea high-tech, especially related technology research on deep-sea fish, is of my country's effective development and utilization of marine biological resources and long-term development are of great strategic significance