title: Morphological background detection and illumination normalization of text image with poor lighting.
abstract: In this paper, some morphological transformations are used to detect the unevenly illuminated background of text images characterized by poor lighting, and to acquire illumination normalized result. Based on morphologic Top-Hat transform, the uneven illumination normalization algorithm has been carried out, and typically verified by three procedures. The first procedure employs the information from opening based Top-Hat operator, which is a classical method. In order to optimize and perfect the classical Top-Hat transform, the second procedure, featuring the definition of multi direction illumination notion, utilizes opening by reconstruction and closing by reconstruction based on multi direction structuring elements. Finally, multi direction images are merged to the final even illumination image. The performance of the proposed algorithm is illustrated and verified through the processing of different ideal synthetic and camera collected images, with backgrounds characterized by poor lighting conditions.
authors.affiliation: State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Microelectronics and Solid-State electronics, University of Electronic Science and Technology of China, Sichuan, China.
authors.forename: Guocheng
authors.initials: G
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Microelectronics and Solid-State electronics, University of Electronic Science and Technology of China, Sichuan, China.
authors.forename: Yiwen
authors.initials: Y
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Microelectronics and Solid-State electronics, University of Electronic Science and Technology of China, Sichuan, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Li
authors.affiliation: State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Microelectronics and Solid-State electronics, University of Electronic Science and Technology of China, Sichuan, China.
authors.forename: Xuanqi
authors.initials: X
authors.lastname: Chen
authors.affiliation: State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Microelectronics and Solid-State electronics, University of Electronic Science and Technology of China, Sichuan, China.
authors.forename: Haitao
authors.initials: H
authors.lastname: Lu
authors.affiliation: Electrical and Computer Engineering, Kaiserslautern University of Technology, Kaiserslautern German Gottlieb-Daimler-Strabe, Kaiserslautern, Germany.
authors.forename: Yanpeng
authors.initials: Y
authors.lastname: Ma
authors.affiliation: State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Microelectronics and Solid-State electronics, University of Electronic Science and Technology of China, Sichuan, China.
authors.forename: Chun
authors.initials: C
authors.lastname: Peng
authors.affiliation: State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Microelectronics and Solid-State electronics, University of Electronic Science and Technology of China, Sichuan, China.
authors.forename: Yijun
authors.initials: Y
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Microelectronics and Solid-State electronics, University of Electronic Science and Technology of China, Sichuan, China.
authors.forename: Linyao
authors.initials: L
authors.lastname: Tang
mesh_terms: D000465:Algorithms; D006801:Humans; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods*; D008029:Lighting; D010363:Pattern Recognition, Automated / Q000379:methods / Q000706:statistics & numerical data*; D010781:Photography / Q000295:instrumentation / Q000379:methods