GA-based adaptive image watermarking with JND profile and fuzzy inference system
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Summary form only given. This paper presents a GA-based adaptive image watermarking technique with just-noticeable distortion (JND) profile and fuzzy inference system (FIS) which is referred to as the GAIWJF technique. During watermark embedding, the GAIWJF technique embeds a watermark into an image by referring to the JND profile of an image so that the technique makes the watermark more imperceptible. The GAIWJF technique employs image features and local statistics to create an FIS containing three fuzzy input variables, eight fuzzy inference rules, and a single fuzzy output variable. During watermark extraction, the GAIWJF technique does not require the information of original images because it employs the FIS to extract watermarks. Also, the FIS is further optimized by a GA so that the performance of watermark extraction can be improved. From experimental results, the GAIWJF technique not only makes the embedded watermark more imperceptible but also possesses adaptive and robust capabilities to resist image manipulations.