3 results about "Blob analysis" patented technology

This invention relates to the field of image processing technology, specifically to a method for detecting through-hole chucks that integrates mask positioning and AI re-inspection. The method involves preprocessing and contour detection of the original workpiece image to achieve coarse positioning of the through-hole region; constructing a multi-layer mask based on the precise geometric information of the through-hole; extracting candidate defect regions through mask subtraction and bitwise AND operations; performing Blob analysis on the candidate defect regions; and conducting multi-dimensional feature analysis and screening based on the physical prior conditions of the chuck to obtain traditional detection judgment results; inputting the through-hole region image into a deep learning model for re-inspection to obtain deep learning detection results; and performing a joint judgment based on the traditional detection judgment results and the deep learning detection results to output the final defect judgment result. This invention achieves precise positioning of the through-hole through multi-layer mask operation and, combined with the joint decision-making of Blob analysis and AI re-inspection, significantly improves the accuracy and robustness of through-hole chuck defect detection while reducing the false detection rate.

This invention relates to the field of industrial defect detection technology, and proposes a cross-scale industrial surface defect detection method and system, including the following steps: acquiring template image I a And the industrial product image to be inspected I b And preprocess it; based on the Blob algorithm, the preprocessed image I a I b Feature extraction is performed to obtain image features I'. a 、I' b The image I is estimated using a Homography estimation neural network. a and I b and image features I' a and I' b Perform alignment calibration separately; for the aligned and calibrated image I a I b The difference image is processed by subtraction, and a sliding window is used to filter noise from the difference image to obtain the industrial surface defect detection result. This invention introduces a Blob analysis algorithm to locate small-scale defects in multi-scale defects, and combines it with a Homography estimation neural network to align and calibrate the standard sample image used for the defect sample to be detected, so as to achieve better difference results.

The application discloses a kind of element pin detection methods based on machine vision, comprising the following steps: step one: using industrial camera obtains the 3D point cloud of the detected element including pin;Step two: based on the 3D point cloud obtained in step one, obtain height map;Step three: in height map, select a height reference value, and form a selection interval on the height reference value according to the set height difference value;Step four: the point cloud of the sampling point in the selection interval determined in step three is used to form a gray scale image;Step five: in the gray scale image, the center of gravity of the pin is obtained using Blob analysis algorithm and center of gravity algorithm;Step six: use the center of gravity of the pin obtained in step five to judge defects, so use height map to set selection interval to select effective point cloud, so noise point cloud can be filtered, avoid noise point cloud adversely affect gray scale image, to form the real gray scale image of pin, and then judge the defects of pin.