Application of computer image processing in office automation system

被引：2
作者：
Zhang M. [1 ]
机构：
[1] Inner Mongolia Electronic Information College, No. 69, Wulanchabu Road, Saihan District, Hohhot, Inner Mongolia
来源：
Automatic Control and Computer Sciences | 2016年 / 50卷 / 3期
关键词：
high definition demonstration of archives; image processing; office automation system;
D O I：
10.3103/S0146411616030081
中图分类号：
学科分类号：
摘要：
With the development of science and technology, a variety of office automation systems (OAS) has been extensively applied in various occasions. Moreover, digital image processing technology has made great progress. The emergence of a series of excellent algorithms represented by Adaboost human face detection algorithm extends the application space of digital image processing in daily work and study. Besides, the operational capability of existing personal computers enables them to run smoothly these algorithms, which further contributes to the technological maturity of the digital image processing associated office automation systems. To keep up with the pace of information technology, this study selects high definition (HD) technology for paper archives in OAS, which is related to digital image processing as the research content. Automatic high definition demonstration of paper archives can reduce the burden on staff. This paper solved the problems of correction of slanted document image, automatic extraction of identification photo and color enhancement of seal and verified the feasibility of the scheme. © 2016, Allerton Press, Inc.
引用
收藏
页码：179 / 186
页数：7
相关论文
共 18 条
  • [1] Cakmak A.F., Benk S., Budak T., The acceptance of tax office automation system (VEDOP) by employees: Factorial validation of Turkish adapted Technology Acceptance Model (TAM), Int. J. Econ. Finance, 3, 6, pp. 107-116, (2011)
  • [2] Do Q.B., Beghdadi A., Luong M., Et al., A perceptual pyramidal watermarking technique, 2008 IEEE International Conference on Multimedia and Expo, pp. 281-284, (2008)
  • [3] Yang J.C., Hou C.P., Shen L.L., Et al., Objective evaluation method for stereo image quality based on PSNR, J. Tianjin Univ., 41, 12, pp. 1448-1452, (2008)
  • [4] Shen H.Y., Sun S.F., Wang J.P., Et al., Comparison of image quality objective evaluation, CiSE 2009. International Conference on Computational Intelligence and Software Engineering, (2009)
  • [5] Suzuki K., Sakamoto Y., Measurement method for objective evaluation of reconstructed image quality in CGH, SPIE OPTO, Int. Soc. Opt. Photonics, pp. 5419-5428, (2013)
  • [6] Haonan T., Sumei L., Objective evaluation method for image quality based on edge structure similarity, Acta Photonica Sin., 42, 1, pp. 110-114, (2013)
  • [7] Rehman A., Saba T., Document skew estimation and correction: Analysis of techniques, common problems and possible solutions, Appl. Artif. Intell., 25, 9, pp. 769-787, (2011)
  • [8] Singh C., Bhatia N., Kaur A., Hough transform based fast skew detection and accurate skew correction methods, Pattern Recognit., 25, 12, pp. 3528-3546, (2008)
  • [9] Saragiotis P., Papamarkos N., Local skew correction in documents, Int. J. Pattern Recognit. Artif. Intell., 22, 4, pp. 691-710, (2008)
  • [10] Al S.A.M., Khairuddin O., Skew detection and correction technique for Arabic document images based on center of gravity, J. Comput. Sci., 5, 5, pp. 363-368, (2009)
12