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Ecological biological recognition method based on R-FCN algorithm

A biometric and ecological technology, applied in the field of biometrics, can solve the problems of slow recognition speed and low accuracy.

Pending Publication Date: 2022-06-03
澜途集思(深圳)数字科技有限公司
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Problems solved by technology

Therefore, it is necessary to identify the organisms of ecological aquatic organisms. The existing ecological biometric identification methods are slow in recognition and low in accuracy.

Method used

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  • Ecological biological recognition method based on R-FCN algorithm
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Embodiment Construction

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments.

[0025] refer to Figure 1-2 , an ecological biometric identification method based on the R-FCN algorithm, including the following steps:

[0026] S1 collects ecological biological features, collects and categorizes the collected ecological features, and establishes a distributed ecological feature database;

[0027] S2 initiates an ecological biometric identification request, and collects biological image data in the ecological environment according to the request;

[0028] S3 processes the collected biological image data to obtain processed biological image data;

[0029] S4 performs target detection on the processed biological image dat...

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Abstract

The invention discloses an ecological biological recognition method based on an R-FCN algorithm, and the method comprises the following steps: collecting ecological biological characteristics, carrying out the collection and classification of the collected ecological characteristics, and building a distributed ecological characteristic database; initiating an ecological biological recognition request, and collecting biological image data in the ecological environment according to the request; processing the acquired biological image data to obtain processed biological image data; performing target detection on the processed biological image data through an R-FCN algorithm; and carrying out comparison identification on the detected biological image data and the feature data in the distributed ecological feature database. According to the method, the full convolution network is used, complete calculation sharing is achieved, the speed is 2.5-20 times higher than that of the Faster R-CNN and reaches 0.17 s / img, the accuracy is slightly improved under the condition of speed advantage compared with that of the Faster R-CNN, the displacement sensitivity of classification and detection is analyzed, and a solution is provided.

Description

technical field [0001] The invention relates to the technical field of biometric identification, in particular to an ecological biometric identification method based on an R-FCN algorithm. Background technique [0002] Aquatic biological communities have an intricate relationship with the water environment and play an important role in water quality changes. Different types of aquatic organisms have different adaptability to water pollution, and some types are only suitable for living in clean water, which are called clear water organisms (or oligopollutants). Some aquatic organisms can live in sewage and are called sewage organisms. The survival of aquatic organisms marks the degree of water quality change, so organisms become indicators of water pollution. Through the investigation of aquatic organisms, the status of water pollution can be evaluated. Many aquatic organisms are very sensitive to water poisons, and they can also be tested by aquatic organism toxicity tests....

Claims

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Application Information

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IPC IPC(8): G06V40/00G06K9/62G06N3/04G06N3/08G06V10/764G06V10/82
CPCG06N3/08G06N3/045G06F18/241Y02A20/152
Inventor 杨志峰沈永明张远蔡宴朋
Owner 澜途集思(深圳)数字科技有限公司
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