HSV Color Feature Extraction in Image Processing with MATLAB Implementation

This is the MATLAB source code for HSV color feature extraction in image processing, implementing the quantization method where the H component is divided into 5 equal segments and S, V components are each divided into 3 equal segments.

In image processing, the HSV color model is a commonly used color representation method. HSV stands for Hue, Saturation, and Value, which correspond to color information, saturation information, and brightness information in images respectively. This course material provides MATLAB source code for extracting HSV color features.

The core algorithm in the source code divides the H component into 5 uniform bins (0-72°, 72-144°, 144-216°, 216-288°, 288-360°) and both S and V components into 3 uniform bins each (0-0.33, 0.33-0.66, 0.66-1.0). This quantization approach effectively extracts color features from images by creating a 5×3×3=45-dimensional feature vector, which can be used for applications like image classification, retrieval, and pattern recognition.

Beyond providing the source code, this course material includes detailed explanations and practical examples to help readers better understand and apply this color feature extraction method. The implementation demonstrates key MATLAB functions such as rgb2hsv() for color space conversion and histogram quantization techniques for feature vector generation.

We hope this course material proves helpful for your image processing projects!