Application Of Edge Detection Algorithm In Apple Grading And Defect Detection

Image processing technology is widely used in our daily life and industrial and agricultural production.Edge detection as an important part of image processing has important theoretical and practical significance.This paper analyzes the advantages and disadvantages of the current classical edge detection algorithms,and proposes an improved fuzzy inference edge detection algorithm,and applies it to apple grading and defect detection.Since there are noises in the collected images,it is necessary to perform filtering before edge detection.However,the traditional non-local mean filtering algorithm has poor filtering effect on images with mixed noise and can not protect the image details.This paper improves the above problems based on the algorithm.Mark the salt and pepper noise points in the mixed noise image,replace the salt and pepper noise pixel values with their neighborhood pixel medians;detect and mark the random noise in the image,and perform iterative filter operation at the noise point when the termination condition is satisfied Output filtered image.Experimental results show that the improved algorithm in this paper has a better filtering effect.Secondly,this paper improves the fuzzy inference edge detection algorithm for traditional fuzzy inference edge detection algorithms such as poor anti-noise performance,non-adaptive threshold setting,and non-single-pixel image edges.The four-direction wavelet transform amplitude obtained by omnidirectional wavelet transform is used as the input of the fuzzy inference system;the adaptive threshold is used to replace the artificially set threshold;and the edge refinement algorithm is used to refine the binary edge image to obtain the final result Edge image.The experimental results show that the proposed algorithm can effectively improve the defects of traditional fuzzy inference edge detection algorithm,and the extracted edge effect is better.Finally,the corresponding algorithm proposed in this paper is applied to apple grading and defect detection.Using this paper to improve the filter algorithm to preprocess the image,get a better initial value image.Edge detection algorithm is used to extract the edge of the filtered apple image,and then it is filled and processed according to the size of apple in the image.Defect detection is achieved by extracting the area where the apple in the color channel is located and then thresholding.In order to facilitate the practical application,this article also uses MATLAB to design the GUI interface.Experiments show that the improved fuzzy reasoning edge detection algorithm proposed in this paper has high noise resistance and accuracy and has strong practical application value.