Source Code for Extracting Wavelet Texture Features and Color Features from Images

The source code provided in this article enables extraction of wavelet texture features and color features from images. These features are essential for various applications in image analysis, image recognition, and image processing. The implementation includes wavelet decomposition algorithms (such as discrete wavelet transform) to capture multi-scale texture information, allowing extraction of detailed texture characteristics and pattern details from images. For color feature extraction, the code typically implements color space conversions (RGB to HSV/CIELAB) and statistical color moment calculations. By extracting wavelet texture features, we can obtain detailed texture information and structural patterns from images, enabling better understanding of image content through multi-resolution analysis. The color feature extraction component helps identify different color regions within images, facilitating color-based segmentation and color processing operations. The code likely includes key functions for feature vector normalization and dimensionality reduction to optimize processing efficiency. Therefore, this source code holds significant importance for research and applications in image processing and computer vision domains, particularly for feature extraction in pattern recognition systems.