Text detection for dust image based on deep learning

doi:10.1109/YAC.2018.8406472

	Text detection for dust image based on deep learning
	Liu, Hao; Li, Ce; Jia, Shengze; Zhang, Dong
	2018-07-06
会议日期	May 18, 2018 - May 20, 2018
会议地点	Nanjing, China
关键词	Deep learning Dust Neural networks Computational costs Convolutional neural network Enhancement algorithms Image enhancement algorithm Intelligent information processing Maximally Stable Extremal Regions Run length smoothing algorithms Text detection
DOI	10.1109/YAC.2018.8406472
页码	754-759
英文摘要	With a large number of images, we rely on the text in images to understand the image quickly and extract useful information. So text detection in images has become one of the important topics of intelligent information processing. With the deteriorating environment, dust weather is more and more common, and text regions in dust images always exit some questions that blur, text features weakened or lost greatly affects our understanding of images and also limits extracting text information from images. Therefore, the traditional algorithm is not good at text detection of dust images. In order to solve these problems, a new method is proposed to detect the dust image text, which is divided into two modules. Firstly, the dust image is enhanced by the dust image enhancement algorithm based on color transfer, and the text and non-text regions in the image are divided by the maximally stable extremal regions, which greatly reduces the computational cost. Next, we choose the text candidate region through convolutional neural network. And then text lines are obtained by the run length smoothing algorithm. Finally, the non-text regions are removed by gaussian smoothing and candidate area filtering to realize text detection in dust images. The experimental results show that the algorithm can be used to detect text regions in dust images with good performance. © 2018 IEEE.
会议录	Proceedings - 2018 33rd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2018
会议录出版者	Institute of Electrical and Electronics Engineers Inc.
语种	英语
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/118031]
专题	能源与动力工程学院
作者单位	College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China
推荐引用方式 GB/T 7714	Liu, Hao,Li, Ce,Jia, Shengze,et al. Text detection for dust image based on deep learning[C]. 见:. Nanjing, China. May 18, 2018 - May 20, 2018.