Method for detecting bin level based on image entropy

Abstract

The invention provides a method for detecting a bin level in an image processing mode based on a digital camera and auxiliary lighting equipment. The method provided by the invention comprises the following steps of: grading the range of a bin by summarizing the characteristics of an image environment of the bin and analyzing the distribution law of the image entropy of defocused images within the full range of the bin in the environment of the bin; controlling the lens focus of the digital camera by a program so that the camera captures images based on grades; preprocessing the images firstly, and extracting feature textures of materials; and calculating the image entropy of the processed images, and finally obtaining a bin level value through analysis and calculation.

Description

technical field [0001] The invention relates to the detection of the material level of a material bin. The invention specifically relates to the detection of the material level of the silo by using a digital camera to take images and perform image processing. Among them, the image preprocessing method is designed according to the material texture characteristics, and the image shooting method is designed according to the image environment characteristics of the silo. Background technique [0002] Silo material level detection is an important measure for safe production. Over the years people have adopted various methods to detect the material level of the silo. Commonly used detection methods are: hammer type, electrode type, capacitive type, machine rod type, weighing type, rotary wing wheel type, radar type, ultrasonic type, laser type, nuclear type, etc. Among them, the hammer type, electrode type, capacitive type, machine rod type, weighing type and rotary wing wheel ...

AI Technical Summary

Problems solved by technology

[0004] (1) The silo has high dust concentration, high humidity, low illumination, poor image quality, and it is difficult for the camera to achieve automatic focus

[0005] (2) The illuminance fluctuates frequently in the silo, for example, there are many large-scale equipment in the coal mine, and the power grid is greatly disturbed, resulting in illuminance fluctuations

[0007] Therefore, due to the special image environment, it is difficult to use ordinary image processing methods for depth measurement to meet the real-time and reliability requirements of silo level measurement, and it is also difficult to achieve long-term and stable detection.

[0008] The patent publication number is CN101270981, which is a material level measurement method and device based on machine vision. It proposes a material level detection method for coal mine underground silos. However, the reliability of this method is difficult to guarantee, so its practical application is limited.

[0011] (1) It is difficult for digital cameras to automatically focus and take reliable images;

[0012] (2) The reliability and precision of the method for measuring material level based on such images are low;

Images