颜色阈值分割流程图 MATLAB和Python

以下是颜色阈值分割的流程图，包括MATLAB和Python的代码实现。

## MATLAB实现

% 加载图像
img = imread('example.jpg');

% 转换为HSV颜色空间
hsv = rgb2hsv(img);

% 提取颜色通道
h = hsv(:,:,1);
s = hsv(:,:,2);
v = hsv(:,:,3);

% 设置阈值
h_threshold = [0.1 0.8];
s_threshold = [0.2 1];
v_threshold = [0.2 1];

% 应用阈值
mask = (h >= h_threshold(1) & h <= h_threshold(2)) & ...
       (s >= s_threshold(1) & s <= s_threshold(2)) & ...
       (v >= v_threshold(1) & v <= v_threshold(2));

% 显示结果
figure;
subplot(1,2,1), imshow(img), title('原图');
subplot(1,2,2), imshow(mask), title('分割结果');

## Python实现

import cv2

# 加载图像
img = cv2.imread('example.jpg')

# 转换为HSV颜色空间
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

# 提取颜色通道
h = hsv[:,:,0]
s = hsv[:,:,1]
v = hsv[:,:,2]

# 设置阈值
h_threshold = [0.1, 0.8]
s_threshold = [0.2, 1]
v_threshold = [0.2, 1]

# 应用阈值
mask = cv2.inRange(hsv, (h_threshold[0]*255, s_threshold[0]*255, v_threshold[0]*255),
                   (h_threshold[1]*255, s_threshold[1]*255, v_threshold[1]*255))

# 显示结果
cv2.imshow('Original', img)
cv2.imshow('Segmented', mask)
cv2.waitKey(0)
cv2.destroyAllWindows()