LBP Features: Local Binary Pattern

MATLAB 3K 232 views 0 downloads 1 credits
Tags:

Resource Overview

LBP features, or Local Binary Patterns, provide a convenient method for texture analysis. After computation, these features are typically described using histograms of local regions, enabling efficient texture classification and pattern recognition in image processing applications.

Detailed Documentation

The article discusses LBP features and Local Binary Patterns, which are highly practical for texture characterization. After calculating LBP values, local region histograms are commonly used to represent these features. Implementation typically involves comparing each pixel with its neighbors using thresholding operations (e.g., `center_pixel > neighbor_pixel ? 1 : 0`) to form binary patterns. Additionally, other image processing techniques can enhance feature representation, such as edge detection algorithms (Sobel, Canny) or advanced texture analysis methods (GLCM, Gabor filters). When processing images, various filters (Gaussian, median) or scale-space approaches (pyramid decomposition) can be employed to capture multi-level feature information. In summary, combining multiple methodologies and techniques enables more comprehensive description and analysis of image characteristics through computational approaches.

You May Also Like