As optical carving character image foreground often consists of high gray-scale pixel region and low gray-scale pixel region
it is impossible to gain character profile correctly with traditional edge extraction method on the basis of gradient
such as Canny operator
and therefore
a kind of image gray-scale transformation method combining false edge information and histogram analysis was introduced. The image foreground after transformation consists of low gray-scale pixel merely. Firstly
feature of Canny edge point was analyzed to extract false edge points. Then histogram analysis of image was performed to determine gray-scale transformation scope and corresponding relationship. Then
smoothness constraints was imposed on boundary region at both sides of false edge to determine gray scale transformation parameters. Finally
on the basis of transformation parameters
gray-scale transformation was carried out on high gray-scale pixel not belonging to background region. Experiment result shows that character strokes after gray-scale transformation consist of low gray-scale pixel merely. Gray-scale transformation at the original boundary is smooth enough and method on the basis of gradient can be used to extract complete and correct character profile.
关键词
Keywords
references
CANNY J F. A computational approach to edge detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(6):679-698.
BERZINS V. Accuracy of laplacian edge detectors[J]. Computer Vision Graphics and Image Processing, 1984, 27(2):195-210.
XU H, FAN T SH. A segment linear function-based on image enhancement method[J].Journal of Liaoning University (Natural Sciences Edition), 2006, 33(4):362-364.(in Chinese)
TANG Q J, LIU J Y, WANG Y, et al.. Infrared image edge recognition and defect quantitative determination based on the algorithm of fuzzy C-means clustering and Canny operator[J]. Infrared and Laser Engineering, 2016, 45(9):0928001-1-5.(in Chinese)
XU H L, CHEN Q, GU G H, et al..High dynamic range image enhancement technology based on guided image filter[J]. Infrared and Laser Engineering, 2015, 44(12):3843-3849.(in Chinese)
SONG X, LUO J, WANG L P, et al.. Line segment detection method based on edge linking[J]. XI Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering & Electronics, 2007, 29(4):559-672.(in Chinese)
ZHOU ZH Y, YANG W CH, WANG Y M, et al.. Realization of face contour tracking by GVF Snake and grey prediction[J]. Opt. Precision Eng, 2011, 19(11):2744-2752.(in Chinese)
VESE L A, CHAN T F. A multiphase level set framework for image segmentation using the mumford and Shah model[J]. International of Computer Vision, 2002, 50(3):271-293.