&lt;title&gt;High-performance distributed memory and computing algorithm for face recognition via conformal mapping&lt;/title&gt;

Megherbi, Dalila B.; Boulenouar, A. J.; Rajagopalan, Venkataramanan

doi:10.1117/12.438263

Cited by 2 publications

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“…Taking automotive water pump screw recognition as an example, the traditional way is to transmit the image data of automotive water pump screws to the cloud through the network for recognition and analysis. Such an approach has high latency and high network bandwidth requirements [4] . By edge computing, the recognition algorithm and model can be deployed on the edge device near the automobile water pump, and the image of the automobile water pump screw can be processed and recognized in real time.…”

Section: Introductionmentioning

confidence: 99%

Edge computing in visual recognition systems

2024

Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024)

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Edge computing is one of the important techniques in visual recognition system. In this paper, the application of edge computing in visual recognition system is introduced by taking the automobile water pump screw recognition as an example. The image is captured by an industrial CMOS camera, the workpiece image is adaptively filtered, and the image RGB to HSV conversion and equalization is carried out based on the feature color, which overcomes the interference of uncertain external factors; the edge computing method based on the feature color realizes the target localization, and the screw recognition method based on the Hough transform is designed, and tested and verified within the QtCreator platform. The results show that the proposed method can effectively recognize screws in the industrial production process with good detection accuracy and real-time performance.

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Section: Introductionmentioning

confidence: 99%