Histogram of oriented gradients (HOG) is a feature descriptor used to detect objects in computer vision and image processing. The HOG descriptor technique counts occurrences of gradient orientation in localized portions of an image - detection window, or region of interest (ROI).
Implementation of the HOG descriptor algorithm is as follows:
Divide the image into small connected regions called cells, and for each cell compute a histogram of gradient directions or edge orientations for the pixels within the cell.
Discretize each cell into angular bins according to the gradient orientation.
Each cell's pixel contributes weighted gradient to its corresponding angular bin.
Groups of adjacent cells are considered as spatial regions called blocks. The grouping of cells into a block is the basis for grouping and normalization of histograms.
Normalized group of histograms represents the block histogram. The set of these block histograms represents the descriptor.
sir i can help u with this project i have done masters in computer engg with specilization in image processing and pattern recognition this is a dummy bid i can give u an exact estimate after we discuss the project hopping for your kind consideration