Design of Coal Briquette Detection Method Based on Vision Technology
To solve the problems of low efficiency,high pollutability and high input efforts in the process of coal selection,and to improve the quality and efficiency of coal selection,an X-ray coal briqutte detection method incorporating Robert's algorithm and thresholding is proposed.Firstly,the coal briqutte detection technologies such as machine vision,X-ray and image segmentation and so on are introduced.Based on the above technologies,the method of sorting thresholds for coal briqutte and gangue is designed.Then,through experiments,the parameters of coal briqutte and gangue,the peak gray level and thickness,the coal briqutte thresholds and gangue thresholds,as well as the system's recognition accuracy of coal briqutte under different thicknesses,are tested.Finally,the cost of the equipment required for the traditional recognition system and the equipment based on the Roberts operator and X-ray recognition system are compared.The experimental results show that the proposed method can reduce the negative impact of object thickness on the recognition results,can further improve the recognition accuracy;can better recognize and distinguish between coal briqutte and gangue,and cost-effective.The method has an important reference value for the identification of coal briqutte detection and can promote the technological development in the field of image recognition and energy utilization to a certain extent.
Machine vision technologyCoal briquette and gangueX-rayRoberts operatorThreshold theoryImage recognition
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