IHOG: Computation of a 3D Orientation Histogram Matrix

IHOG (Integral Histogram of Oriented Gradients) generates a three-dimensional matrix representing orientation histograms across the image. This matrix stores cumulative histogram values for each pixel position, essentially creating an integral image structure for gradient orientation distributions. The implementation typically involves computing gradient magnitudes and orientations across the image using convolution with Sobel or similar kernels, followed by binning orientations into histogram channels. The integral histogram approach allows for rapid calculation of orientation features within arbitrary rectangular regions through simple arithmetic operations on the cumulative values, making it particularly efficient for sliding window detection algorithms. This comprehensive representation of spatial orientation information serves as a fundamental component in various computer vision pipelines, including object detection, texture analysis, and feature matching applications.