Detecting of pellet size based on image enhancement and improved Hough detection algorithm
To address the issues of overexposure distortion and challenging identification of pellet adhesion in pellet images,an enhanced contrast-limited adaptive histogram equalization method was proposed for image enhancement,along with the introduction of a multi-scale Hough detection algorithm for efficient pellet detection.Firstly,the en-hanced contrast-limited adaptive histogram equalization method incorporates a detail security mechanism by utilizing a contrast enhancement function to adjust the output of contrast-limited adaptive histogram equalization(CLAHE).The extent of contrast improvement is limited by this approach,while simultaneously preserving more detailed infor-mation in the images.Then,the image noise induced after enhancement is filtered by the adaptive median filtering method.Finally,the multi-scale Hough detection algorithm is applied to tackle both adhesion pellet identification and detection challenges,so as to realize the accurate,real-time and efficient detection and statistics of pellet size.Practical application results from a steel factory reveal that this method achieves a precision rate of as high as 94.44％,with 96.72％accuracy in determining the number of qualified pellets,fulfilling the requirements of pellet preparation process.This method plays a vital role in enhancing production effectiveness,decreasing labor expen-ses,and enhancing overall quality control rates for pellet preparation.
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