Journals
  Publication Years
  Keywords
Search within results Open Search
Please wait a minute...
For Selected: Toggle Thumbnails
Image segmentation for complex voids and pits of bridge based on combination of HSI color space and gray fluctuation
YAO Xuelian, HE Fuqiang, PING An, LUO Hong, WAN Silu
Journal of Computer Applications    2019, 39 (3): 882-887.   DOI: 10.11772/j.issn.1001-9081.2018081688
Abstract472)      PDF (968KB)(262)       Save

As the voids and pits image of bridge often has uneven illumination and multi-background interference problems, an image segmentation algorithm for complex voids and pits of bridge was proposed based on HSI color space and gray fluctuation. Firstly, S-component gray curve was plotted and all the potential peaks and troughs of the curve were searched, then the height differences between adjacent peaks and thoughs were calculated. Secondly, partial height differences were selected based on the standard deviation of gray pixel difference value. Finally the threshold segmentation of image was finished by searching the best threshold based on the standard deviation of partial height differences. Experimental results show that the proposed algorithm has better segmentation effect and real-time performance than OTSU, Niblack and Tsallis entropy method.

Reference | Related Articles | Metrics
Scrambling algorithm based on layered Arnold transform
ZHANG Haitao YAO Xue CHEN Hongyu ZHANG Ye
Journal of Computer Applications    2013, 33 (08): 2240-2243.  
Abstract810)      PDF (750KB)(473)       Save
Concerning the safe problem of digital image information hiding, a scrambling algorithm based on bitwise layered Arnold transform was proposed. The secret image was stratified by bit-plane, taking into account the location and pixel gray transform, each bit-plane was scrambled for different times with Arnold transforma, and the pixel was cross transposed, and adjacent pixels were bitwise XOR to get a scrambling image. The experimental results show that the secret image histogram is more evenly distributed after stratification scrambling, its similarity with the white noise is around 0.962, and the scrambling image can be restored and extracted almost lossless, which improves the robustness. Compared with other scrambling algorithms, the proposed algorithm is more robust to resist attack, and improves the spatial information hiding security.
Reference | Related Articles | Metrics