Water quality toxicity detection method based on fish activity analysis

Abstract

Disclosed is a water quality toxicity detection method based on fish activity analysis. The method comprises the following steps that 1, crucian is adopted as a biological monitoring object so as to be subjected to real-time monitoring; 2, a target crucian contour is extracted through conversion from RGB to HSV color space, crucian groups are monitored in real time, and a crucian tracking video sequence is obtained; 3, crucian motion data analysis and detection are performed, wherein 3.1, differences among the crucian velocity speed, a counter area and an area mean value are adopted as main characteristic data; 3.2, a mature detection model is generated on the basis of a Naive Bayes classifier algorithm; 3.3, novel characteristic data is adopted for detecting and judging whether the detection model is mature or not; 3.4, real-time water quality data is detected in an online mode through the mature detection model, and finally online detection of the water quality toxicity is achieved. Online real-time detection can be achieved, sensitivity and continuity of water quality detection can be improved, the detection cost can be lowered, and real-time effective detection can be performed on a large number of unknown water quality toxicity conditions.

Description

technical field [0001] The invention relates to the fields of biological water quality detection, HSV space domain transformation and extraction contour, naive Bayesian classification technology and the like, and proposes a biological water quality toxicity detection method. Background technique [0002] Water quality anomaly detection is based on the normal data index of the monitored water quality, and determines whether an abnormal water quality has occurred by checking the deviation degree between the current data index of water quality and the normal data index. Water quality detection can be simplified as a classification problem, the input is water samples, and the output is normal water quality or abnormal water quality. [0003] Most of the traditional water quality testing methods use physical and chemical testing combined with statistical model analysis to extract and test water quality data. The shortcomings of the traditional method are: 1. Most of the water qu...

AI Technical Summary

Problems solved by technology

The shortcomings of the traditional method are: 1. Most of the water quality data collection is manually collected regularly, resulting in a lag in collection and cannot cope with the detection of sudden water pollution; 2. Due to the use of physical and chemical detection, a series of analysis, Testing equipment, resulting in higher testing costs

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