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Image analysis and recognition

This project received 30 bids from talented freelancers with an average bid price of $147 USD.

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Project Budget
$10 - $30 USD
Total Bids
30
Project Description

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.

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