Abstract
The communication recognition of mobile phone core is a test of the development of machine vision. The size of mobile phone core is very small, so it is difficult to identify small defects. Based on the in-depth study of the algorithm, combined with the actual needs of core identification, this paper improves the algorithm and proposes an intelligent algorithm suitable for core identification. In addition, according to the actual needs of core wire recognition, this paper makes an intelligent analysis of the core wire recognition process. In addition, this paper improves the traditional communication image recognition algorithm and analyzes the data of the recognition algorithm according to the shape and image characteristics of the mobile phone core. Finally, after constructing the functional structure of the system model constructed in this paper, the system model is verified and analyzed, and on this basis, the performance of the improved core recognition algorithm proposed in this paper is verified and analyzed. From the results of online monitoring and recognition, the statistical accuracy of mobile phone core video recognition is about 90%, which has higher accuracy in mobile phone core image recognition than traditional recognition algorithms. The core line recognition algorithm based on deep learning and machine vision is effective and has a good practical effect.
Highlights
In recent years, with the advent of the era of smart mobility, smartphone applications have become more and more widespread, the frequency of use has become higher and higher, and the overall power consumption has been increasing
A lot of white dust is attached to the surface of several wires, which will cause a great interference to color recognition. erefore, the current misjudgment rate of the position of several wires of this type of equipment is very high, resulting in a large number of defective products in the production process
There has been no substantial progress. e main reason why the recognition rate of the positions of several wires cannot be improved is mainly due to color difference and white dust interference [2]. e main reason why the automatic detection of copper wire riveting cannot be realized is that the copper wire and the riveting piece are made of metal, and the colors are similar, which cannot be clearly distinguished in the image
Summary
With the advent of the era of smart mobility, smartphone applications have become more and more widespread, the frequency of use has become higher and higher, and the overall power consumption has been increasing. Mobile phone core wire manufacturers are actively introducing or developing efficient machine vision technology to improve the recognition rate of the positions of several wires and realize automatic detection of copper wire riveting. If the position relationship between the data cable core and the internal solder joint of the terminal is not accurate during the welding process, the data cable will inevitably fail to achieve its due function and meet the quality standard and will eventually be treated as waste. If it continues to be misused, the electronic equipment connected to it will be at risk of damage. With the support of in-depth learning algorithm, this paper constructs a communication core line recognition system suitable for automatic recognition, which can be used in the manufacturing industry
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