Implementation of Dalal's HOG Feature Algorithm
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Resource Overview
Developed based on Dalal's HOG feature algorithm, this code features simple implementation with clear comments. By modifying the image path parameter, it generates a 36×105 feature vector suitable for image processing applications.
Detailed Documentation
This implementation follows Dalal's Histogram of Oriented Gradients (HOG) feature algorithm, designed with straightforward code structure and comprehensive commenting for easy understanding. The core algorithm computes gradient magnitudes and orientations across image cells, then constructs histograms that are normalized within blocks to create illumination-invariant descriptors. By adjusting the input image path parameter in the configuration section, the program generates a compact 36×105 feature vector that captures essential shape and texture information. This feature vector serves as effective input for various computer vision tasks including object detection, classification, and pattern recognition. The implementation includes key functions for gradient computation, bin assignment, and block normalization, following the standard HOG pipeline with optimized parameters for efficient feature extraction.
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