Histogram of gradient magnitudes: A rotation invariant texture-descriptor
Monika Sharma, Hiranmay Ghosh · 2015
We propose a new low-dimensional rotation invariant local texture-descriptor with a low computational complexity in this paper. Commonly used local texture features are sensitive to rotation of texture patterns in an image. On the other hand, rotation-invariant features are generally computationally expensive. The proposed feature descriptor is based on gradient of magnitude of pixel-intensities that is naturally rotation-neutral. Experiments with several datasets show better performance for the proposed texture-descriptor as compared to the existing texture-descriptors in image classification and segmentation tasks.