Rotation, scaling, and translation invariant local watermarking technique with Krawtchouk moments

A rotation, scaling, and translation invariant local watermarking is proposed with one or two Krawtchouk moment(s) of the original to estimate the geometric distortion parameters including rotation angle, scaling factor, and translation parameter. Krawtchouk moments can be used as private key of watermark extractor. Watermark is inserted into perceptually significant Krawtchouk moments of original, and watermark based on Krawtchouk moments is local. Independent component analysis (ICA) is utilized to extract watermark blindly. Experimental results show that this method has a good robustness against distortions preformed by watermark benchmark—Stirmark.     

基于边缘区域不变矩的缺损扩展目标识别方法

 该方法提出以基于边缘区域的局部不变矩作为识别特征，结合多神经网络实现对缺损扩展目标的有效识别。讨论了离散情况下基于边缘区域局部不变矩的平移、旋转和尺度不变性。在此基础上，建立目标多个处理区域的BP人工神经网络，利用各网络分类综合结果提高缺损目标的识别率。实验结果显示该方法能够对缺损扩展目标进行正确识别，特别对于有较大部分缺损的扩展目标识别有明显优势。