imagemerge1 indicates the preliminary merged image, imagemerge2 represents the merged image, k1 denotes the weight coefficient of image1, k2 represents the weight coefficient of image2, a stands for the stretching coefficient, and b indicates the stretching offset; image1 refers to the convex image for flaw detection, while image2 denotes the end face image.

According to one aspect of the invention, the step s2 includes:

s21: Utilize a layer scanning camera to capture multiple images of the lens interior along the Z-axis, and then divide them into multiple groups sequentially.

s22. Segment and identify defects in each set of images, placing all defects that meet the defect criteria into the defect container.

s23, In the defective container, product flaw detection is performed by filtering out defects at the same location through comparison of the deviation value of the defect center distance.

s24: Filter defects appearing clear at the same location using clarity algorithms, surface blemish detection system; judge whether the size of this defect qualifies it as a defective product.

s11. Create template images on the end face or dome of the lens to obtain end face images and dome images, and then perform matching and positioning.

Align the image of the boss after performing an affine transformation;

s13. Extract high-frequency components from the face image according to the custom nuclear extraction.

Utilize the weighted average algorithm to overlay the end face image and the convex platform image to obtain the fused image.

s15, Inspect for defects based on the integrated image as described.

We are a Taiwan R&D and business team led by Zhao Jufeng from Hangzhou Dianzi University.

According to one aspect of the invention, the flaw detection system, in step s33, the method for segmenting the detection image includes global threshold segmentation, dynamic threshold segmentation, or mean threshold segmentation methods.

This invention's lens defect detection method allows for comprehensive inspection of the lens, including surface and dome defects, as well as defects like dust, internal dirt, demolding, and fibers within the lens area. It also detects damage to the lens, adhesive, and barrel, as well as the upper and lower surfaces of the lens. The method boasts high precision and other advantages.

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