图像lbp纹理特征提取python代码
时间: 2024-09-15 18:14:56 浏览: 121
python实现LBP方法提取图像纹理特征实现分类的步骤
LBP(Local Binary Pattern,局部二值模式)是一种常用的颜色和灰度图像纹理描述符,在Python中可以使用OpenCV库来实现。以下是一个简单的LBP特征提取的Python代码示例:
```python
import cv2
import numpy as np
def extract_lbp(image_path):
# 读取图像
img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
# 确定LBP邻域大小(通常为3x3)
neighborhood_size = 3
# 计算LBP码
def compute_lbp(pixel, neighbors):
mask = [(1 << i) if pixel >= neighbors[i] else 0 for i in range(8)]
return np.sum(mask)
# 应用LBP算法
lbp = np.zeros(img.shape)
for y in range(1, img.shape[0] - 1):
for x in range(1, img.shape[1] - 1):
center_pixel = img[y, x]
neighbors = [img[y + dy, x + dx] for dy, dx in [(-1, -1), (-1, 0), (-1, 1), (0, -1), (0, 1), (1, -1), (1, 0), (1, 1)] if (y + dy, x + dx) in zip(*np.where(img > 0))]
lbp[y, x] = compute_lbp(center_pixel, sorted(neighbors))
return lbp
# 使用示例
image = 'your_image_path.jpg'
lbp_features = extract_lbp(image)
```
这个代码首先将输入图像转换为灰度,然后对每个像素及其周围邻居计算LBP值。`compute_lbp`函数用于实际的LBP计算,最后返回的是整个图像的LBP表示。
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