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ISSN      1003-9775
CN        11-2925/TP
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基于Retinex灰度增强和颜色信息的时空上下文跟踪算法

张红颖, 胡文博
(中国民航大学电子信息与自动化学院 天津 300300)
分类号: TP391. 41
出版年,卷(期):页码: 2017 , 29 ( 12 ): 2323-2329 张红颖
摘要: 针对光照变化下图像局部或整体灰度剧烈变化而容易导致目标跟踪失败的问题, 提出一种结合颜色信息和Retinex灰度增强的改进时空上下文算法. 首先比较单尺度Retinex算法和多尺度Retinex算法, 确定使用多尺度Retinex算法对图像进行灰度增强以减弱光照变化对图像灰度的影响; 然后比较各种视觉模型的颜色特征, 确定引入基于色相信息的目标模型, 并将该模型与多尺度Retinex灰度增强模型相结合作为跟踪的目标模型. 实验结果表明, 文中算法比原算法在跟踪成功率上有较大提升, 在Shaking场景下跟踪成功率为95%, 比传统的时空上下文跟踪算法的跟踪成功率提高约24%; 相比其他主流算法, 该算法在平均跟踪成功率和跟踪精度上的表现也更高、更可靠.
关键词: 机器视觉; 目标跟踪; 时空上下文; 光照变化; Retinex
Spatio-temporal Context Tracking Algorithm Based on Retinex-enhanced Gray Information and Color Information
Zhang Hongying and Hu Wenbo
(College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300)
abstract: Illumination variation may result in extreme changes of local or overall image intensity, thus leads to tracking failure. To solve this problem, a spatial-temporal context (STC) tracking algorithm combing with color information and Retinex-enhanced gray information is proposed. Firstly, by comparing and analyzing the sin-gle-scale Retinex algorithm and multi-scale Retinex algorithm, the multi-scale Retinex algorithm is used to enhance image gray level to reduce illumination change influence on image gray level. Then, on this basis, by comparing the color features of various visual models, target model is adopted by hue information. Target tracking model is combined with model enhancement and multi-scale Retinex gray enhancement model. Finally, experimental results show that the proposed algorithm has a higher success than original algorithm. For example, algorithm success rate is about 95% in the Shaking scenario, which is about 24% higher success rate than STC. In comparison with other algorithms, it has better performance and higher tracking accuracy.
keyword: machine vision; object tracking; spatial-temporal context; illumination variation; Retinex
 
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