Abstract
Image recognition is a research hotspot in the field of vision. Its fundamental task is to classify and identify the scenes or targets contained in images by the help of computer. It has a wide implementation expectation in content-based image recognition, intelligent environment perception, positioning of military bases, and other locations. In this paper, many studies are conducted on computer vision-based image recognition, combining multi-position science, optical projection, and optical consistency. For example, based on the visual consistency of the recognition, for the recognition process of feature extraction, recognition model, visual prominence, and other problems, this paper proposes the corresponding solution, from the in-depth study of the visual consistency of the image recognition engine results. The method first computes the target image of the result returned by the recognition machine and uses the target image for the initial purpose. Next, the visual consistency function for all images in the set. Finally, a set of images was created as an image recognition result. It has been proved that the algorithm optimized algorithm in this paper can identify more feature points, about 4–6 times that of conventional algorithms.
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Tan, G., Liu, Y., Sridevi, S. (2023). Computer Vision on Image Recognition Technology. In: Jansen, B.J., Zhou, Q., Ye, J. (eds) Proceedings of the 2nd International Conference on Cognitive Based Information Processing and Applications (CIPA 2022). CIPA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 155. Springer, Singapore. https://doi.org/10.1007/978-981-19-9373-2_6
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DOI: https://doi.org/10.1007/978-981-19-9373-2_6
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