A visual inspection method for IC defects in transparent packaging
A visual inspection and defect technology, applied in the field of inspection, can solve the problems of high workload of workers, low inspection efficiency, poor stability of inspection results, etc., and achieve the effect of improving production efficiency and production quality, high inspection efficiency and fast inspection speed.
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Embodiment 1
[0029] see Figure 1-Figure 2 , the visual detection method of the transparent encapsulation IC defect of the present invention, comprises the following steps;
[0030] (1) Place the product to be tested on the testing equipment, and select different visual devices according to the different sides of the product to collect the image information of each side of the product, and upload the collected image information to the processor ;
[0031] (2) After the processor receives the image information, it compares the image information with the standard image of OK products to find out the defective products, and selects the corresponding algorithm for the defects existing in each surface of the product. The process is as follows:
[0032] Firstly, according to the differences in the background on the texture of the image information, the gray level co-occurrence matrix is used to calculate the following four different texture representation features in the image information: ...
Embodiment 2
[0059] In this embodiment, a specific case is used to illustrate the visual inspection method for the defect of a transparent packaged IC of the present invention:
[0060] Taking the scratch on the front as an example, after the visual device in Example 1 detects that there is a defect on the front of the product, the algorithm can detect that there is a defect in a specific area on the front of the product, but it is not sure what kind of defect it is, because There are still defects such as dirt and air bubbles on the front side. At this time, it can be judged according to the shape and gray value changes of the defects. For example, air bubbles and scratches will cause the local gray value to increase, and dirt will cause the local gray value to decrease. , and the bubbles are usually round, the scratches are linear, and the dirt has no fixed shape. At this time, if the algorithm judges that the defect causes the local gray value to become higher, and the defect is linear,...
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