Abstract
In this study, an improved image blind identification algorithm based on inconsistency in light source direction was proposed. And a new method defined as “neighborhood method” was presented, which was used to calculate surface normal matrix of image in the blind identification algorithm. For an image, there is an error function between its actual light intensity and calculated light intensity, and for different light source models, there are different constraint functions of light. Light source direction which makes both error function and constraint function get the minimum is the one we want to seek. On this basis, according to the error function and the corresponding constraint function, search means and the Hestenes–Powell multiplier method were used in the improved algorithm to calculate the light source direction for local and infinite light source images, respectively. Further, the authenticity of image can be determined by the inconsistency in light source direction of different areas in the image. Experimental results showed that the light source direction of different areas in an image could be calculated accurately, and then the image tampering can be detected effectively by the improved algorithm. Moreover, the performance of the improved algorithm of the proposed blind identification is superior to that of the existing one in terms of detection rate and time complexity.
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Lv, Y., Shen, X. & Chen, H. An improved image blind identification based on inconsistency in light source direction. J Supercomput 58, 50–67 (2011). https://doi.org/10.1007/s11227-010-0531-y
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DOI: https://doi.org/10.1007/s11227-010-0531-y