Feature Detection by Color Tensor-Based Photometric Invariants

Although the majority of images are recorded in color format nowadays, computer vision research is still mostly restricted to luminance-based feature detection. In this paper, we combine the features based on the color tensor with photometric invariant derivatives to arrive at photometric invariant features. The combination of the photometric invariance theory and tensor based features allows for detection of a variety of features such as photometric invariant edges, corners. Experiments show that the proposed features are robust to scene incidental events and perform well in real-world scene.