Text Detection for Dust Image Based on Deep Learning

CORC > 兰州理工大学 > 兰州理工大学 > 新能源学院

	Text Detection for Dust Image Based on Deep Learning
	Liu, Hao; Li, Ce; Jia, Shengze; Zhang, Dong
	2018
关键词	dust image enhancement algorithm text detection
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.
会议录	PROCEEDINGS 2018 33RD YOUTH ACADEMIC ANNUAL CONFERENCE OF CHINESE ASSOCIATION OF AUTOMATION (YAC)
会议录出版者	IEEE
会议录出版地	345 E 47TH ST, NEW YORK, NY 10017 USA
语种	英语
资助项目	National Natural Science Foundation[61365003] ; Gansu Provincial Basic Research Innovation Group[1506RJIA031]
WOS研究方向	Automation & Control Systems
WOS记录号	WOS:000454639700137
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/36144]
专题	新能源学院能源与动力工程学院电气工程与信息工程学院
通讯作者	Li, Ce
作者单位	Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou, Gansu, Peoples R 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:.