高品质指针式仪表识别分析与研究

随着计算机信息技术的高速发展,高效的智能化算法越加在社会各方面发挥着重要的建设作用,也深刻地影响着社会的技术改造。在此对于诸多的传统行业也越发发生着深刻地变化。尤其表现在高品质的视觉算法上,通过高品质的指针式仪表识别可较为高效地实现对多场合的仪器仪表达到精确地监控并且通过该类技术也可较大程度地改善现行多场合的仪表无法实现实时有效监控的落后现状。在此就针对指针式监控中的相关干扰要素、转换为视频图像的模糊现象进行全局化的分析,在不断的实现深度学习与图像处理技术的技术上,而实现对于相关设备图像的类别的高品质精确性识别。在此对于基本性的深度学习算法展开分析的同时,结合实际的图像特征提取分析,实现相关仪表的高品质图像跟踪、识别,从实用性的理论及应用角度进行切入,为后相关算法深入研究奠定实践基础。

Analysis and Research on the identification of high quality pointer meters

With the rapid development of computer information technology,efficient intelligent algorithm plays an important role in all aspects of society,and also has a profound impact on the technical transformation of society.In this regard,many traditional industries are also undergoing profound changes.Especially in the high-quality visual algorithm,through the high-quality pointer type instrument recognition,it can be more efficient to achieve accurate monitoring of multi occasion instruments and meters,and through this kind of technology,it can also greatly improve the current situation that multi occasion instruments can not achieve real-time effective monitoring.In this paper,aiming at the relevant interference elements in pointer monitoring and the fuzzy phenomenon of converting to video image,the global analysis is carried out.In the continuous realization of deep learning and image processing technology,the high-quality and accurate recognition of the categories of related equipment images is realized.At the same time of analyzing the basic deep learning algorithm,combining with the actual image feature extraction and analysis,we can realize the highquality image tracking and recognition of related instruments.From the perspective of practical theory and application,we can lay a practical foundation for the in-depth study of related algorithms.