山东大学学报 (工学版) ›› 2022, Vol. 52 ›› Issue (6): 183-190.doi: 10.6040/j.issn.1672-3961.0.2021.359
• 电气工程 • 上一篇
何子亨1,孙丽丽1,左修洋2,刘鸿雁1,王雨晨1,车四四1,王朔1
HE Ziheng1, SUN Lili1, ZUO Xiuyang2, LIU Hongyan1, WANG Yuchen1, CHE Sisi1, WANG Shuo1
摘要: 为提高运维效率,针对视频中的分会场文字信息,采用计算机视觉技术,识别出分会场的名称,以便实现轮询视频的自动检测。提出一种基于隐马尔可夫模型(hidden Markov model,HMM)的轮询视频分会场名称识别算法,利用分会场名称中相邻单个文字的相关性,提高分会场名称的识别准确率。对每帧视频图像,采用微分二值化(differentiable binarization,DB)算法定位文字区域,提取单个文字的分块特征,并通过计算欧式距离进行单字识别。考虑分会场名称中相邻文字之间的相关性,构建HMM,实现相邻文字之间的关联,并采用Viterbi算法计算分会场名称识别结果。试验数据表明,在采用较低维数的特征向量时,本研究提出的分会场名称识别算法具有较高的识别率和较强的抗噪性能。
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