Extracting Image Texture Features Using Gray-Level Co-occurrence Matrix
- Login to Download
- 1 Credits
Resource Overview
Image texture feature extraction based on Gray-Level Co-occurrence Matrix, where FC represents the generated feature vector with implementation insights
Detailed Documentation
In this paper, we implement a Gray-Level Co-occurrence Matrix (GLCM)-based approach to extract texture features from images. The methodology involves calculating spatial relationships between pixel intensity pairs at specific offsets and orientations. We compute the feature vector FC to represent these extracted characteristics, which typically includes statistical measures such as contrast, correlation, energy, and homogeneity derived from the GLCM. This approach provides valuable insights into image texture patterns and plays a crucial role in subsequent analysis and processing tasks. The implementation can be optimized using vectorized operations for efficient computation of co-occurrence probabilities across multiple directions.
- Login to Download
- 1 Credits