Image-based chip information rapid acquisition and identification method

Abstract

The invention discloses an image-based chip information rapid acquisition and identification method, which comprises the following steps of: 1, establishing a chip image acquisition device, and acquiring images of N types of chips through a camera in the device; 2, collecting video information of N types of chips; 3, converting the chip video into a plurality of pictures, and screening out the pictures of which the chips are not shielded and the images are not blurred to generate a chip model picture data set; 4, establishing a deep learning chip identification model, dividing the chip model picture data set into a training set and a test set, performing model training by using the training set, and storing model parameter values; 5, verifying the performance of the chip identification model by using the test set; and 6, acquiring photos of different types of chips to be identified by using a chip image acquisition device, and inputting the photos into the chip identification model toidentify the types of the chips. According to the invention, the influence of environmental factors such as background and light can be effectively eliminated, and the chip identification function isrealized.

Description

technical field [0001] The invention belongs to the technical field of electronic device identification, and in particular relates to an image-based chip information rapid collection and identification method. Background technique [0002] Most of the current chip identification methods are mainly implemented using pattern matching algorithms. In the pattern matching algorithm, the image processing technology is mainly used to perform a series of operations such as grayscale, binarization, rotation, and zooming on the image, and then the image matching algorithm is used to obtain the edge of the chip, so as to realize the positioning and identification of the chip. Chip recognition by pattern matching has been widely used in actual production, and the accuracy of chip recognition in a stable environment is extremely high. However, these algorithms mainly extract the edge of the chip, so there are strict requirements on light and background, and the adaptation to changing sce...

AI Technical Summary

Problems solved by technology

Generally, the recognition methods of the existing chip pattern matching methods operate inside the device, and the recognition environment is relatively stable, and cannot achieve accurate recognition in environments with large changes in background and light conditions.

Images