An anaglyph image is typically created by combining the color channels from a pair of stereo images to create a new three-channel image. Presently, when an imaging system encounters a three-channel image (such as a JPEG image), it is treated in a similar fashion as is any other three-color image. There currently is no method for determining whether the image is an anaglyph image or a single-view image. In this paper, we propose a set of features for detecting anaglyph images. The algorithm extracts features based on stereo matching, edge coincidence between channels, channel correlation, and distributions of chroma values. On an independent test set with an even number of anaglyph and non-anaglyph images, the algorithm achieves a recognition accuracy of 95.2%.
In one particularly related work, REF uses stereo analysis between channels of an image to determine if the image is a stereo anaglyph or not.
Detecting anaglyph images with channel alignment features
2010 IEEE International Conference on Image Processing
2010 IEEE International Conference on Image Processing
Computer Science