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Multiple Watermark Detection Robots by SPAMSVM Model for DCT, Histogram and LSB Method

Watermarking technology has been widely used to protect image copyrights. However, to extract a watermark from an image requires previous information on the technique used for embedding the watermark. Without the information the extraction process could be time consuming and less accurate. This paper proposed SPAMSVM model that can effectively and accurately identify a variety of watermarking techniques. The model made of the SPAM and SVM techniques to extract image feature values to train for detect. Experimental results showed that the proposed model can effectively identify the watermarking techniques used in the image embedment. Most were accurately identified with some minor errors in the histogram and LSB techniques. In future, more watermark techniques will be used for training, in order to identify more watermarking techniques and to improve accuracy.