| dc.description.abstract | With the advent of Global Industry 4.0, the use of big data, the Internet of Things, and robots is also in full swing. How to improve the production capacity and quality of the factory is already the most important issue for every company. The company must transform or be submerged in the torrent of times.
In this study, in order to enable the inspectors and engineers in the factory to quickly identify the quality status of the product, we used Matlab image processing powerful functions to process the collected photos for digital image processing, including the following functions (binarization, morphology, edge processing, analysis of entropy value, etc.), these functions can be used to identify the defects of the AMB heat dissipation substrate faster and speed up the inspection time of the production line for index. The next goal of our efforts will be to use the results of this research, and then to develop neural network or other wavelet processing for image recognition learning and recognition verification. | en_US |