ローカルバイナリパターン（LBP）は、広く使われている強力なテクスチャ記述子です。 画像処理で and コンピュータビジョン. It encodes the local structure of an image by comparing each pixel’s intensity with its neighboring pixels. The basic idea behind LBP is to create a binary pattern for each pixel in the image based on the intensity of its neighbors, allowing for efficient texture classification.
To compute LBP, each pixel in the image is compared to its surrounding neighbors (typically the 8 closest pixels). If a neighbor’s intensity is greater than or equal to the central pixel, it is assigned a value of ‘1’; otherwise, it is assigned ‘0’. These binary values are then concatenated to form a binary number, which is converted to a decimal value. This value represents the LBP code for that pixel.
The resulting LBP histogram captures the distribution of these codes across the entire image, providing a コンパクトな表現 of texture information. LBP is particularly effective for tasks such as face recognition and image segmentation due to its robustness against monotonic changes in illumination.
Variants of LBP, such as Uniform LBP and LBP Variance, have been developed to enhance its discriminative power and reduce sensitivity to noise. Overall, LBP has become a cornerstone technique in the field of computer vision, enabling various applications in 物体認識, surveillance, and medical imaging.