DETECTING THE COMPOSITE OF PHOTOGRAPHIC IMAGE AND COMPUTER GENERATED IMAGE COMBINING WITH COLOR , TEXTURE AND SHAPE FEATURE
DETECTING THE COMPOSITE OF PHOTOGRAPHIC IMAGE AND COMPUTER GENERATED IMAGE COMBINING WITH COLOR , TEXTURE AND SHAPE FEATURE
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DOI：
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发表时间：
2013
影响因子：
5.6
通讯作者：
Yongzhen Ke;Weidong Min;Xiuping Du;Zhen-wen Chen
中科院分区：
文献类型：
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作者：
Yongzhen Ke;Weidong Min;Xiuping Du;Zhen-wen Chen
随着计算机图形学技术的发展和计算机图形学（CG）与摄影图像视觉差异的缩小，计算机图形学与摄影图像的拼接越来越普遍，这就需要对计算机生成的图像与真实的照片进行自动区分。基于颜色、纹理和形状等视觉特征，采用后验概率支持向量机（PPSVM），提出了一种对摄影图像和计算机生成图像进行分类和局部伪造检测的方法。这些特征是从800幅计算机生成的图像和800张照片中获得的，并用于用PPSVM训练和测试图像样本。PPSVM可以计算图像属于摄影图像或计算机生成图像的概率。通过设置概率阈值，可以得到分类结果。颜色、纹理和形状特征的分类准确率分别为76.75%、85.25%和69%。结合颜色、纹理和形状特征，识别率提高到89.375%。本文提出的分类方法被用于检测摄影图像中CG元素的局部边界复合，并用于检测签证。实验结果表明，该方法是有效的，具有良好的检测率的PG和CG的局部forward复合。它还具有低维特性和低时间复杂度。
With the development of computer graphic techniques and smaller visual difference between photographic images (PG) and computer graphics (CG), splicing of computer graphics and photographic is becoming more common, which causes the need for automatically distinguishing computer generated images from real photographs. Based on several visual features that derived from color, texture and shape feature, using posterior probability support vector machine (PPSVM), this paper presents a method for classification of photographic image and computer generated images, and detection of local forgery composite of them. These features are obtained from 800 computer generated images and 800 photographs, and used to train and test the image samples with the PPSVM. The PPSVM can calculate the probability of image belonging to photographic images or computer generated images. We can achieve the result of classification by setting a threshold of probability. The classification accuracies for color, texture and shape features are 76.75%, 85.25% and 69% respectively. The accuracy is improved to 89.375% with combined color, texture and shape features. The proposed classification method is used to detect the local forgeries composite of the CG elements in photographic, and vice visa. Experimental results show that the proposed method is efficient with good detection rate of local forgeries composite of the PG and the CG. It also possess low dimensional features and low time complexity.