Image feature extraction based on spectral graph information

Graphs have been widely used in image processing and understanding tasks. We introduce a novel graph generation model which greatly reduces the size of the traditional pixel-based graph. Based on the generated graph, we propose two feature extraction methods which utilize spectral graph information, and apply the features to image. Experiments show that our proposed oscillatory image heat content and weighted heat content spectrum features are more robust to small distortions and changes of viewpoint than the image heat content feature we proposed previously. The features are also capable of capturing important image structural information of the image and perform well alone or in combination with other low-level image features.