Harris特征提取

data/1.OpenCV初阶/4.几何变换和图像特征/3.图像特征与特征提取/harris.md

+# 提取亭子瓦片特征
+
+下图是一个湖边的亭子，通过 OpenCV 的 Harris 特征提取可以提取到亭子的瓦片特征
+
+![](./tower.jpeg)
+
+上图背景图里的植被的角点也会被 Harris 特征提取到，因此我们先用之前学习过的知识过滤出前景图后再做 Harris 特征提取，过程图片如下：
+
+![](./tower_harris.jpeg)
+
+框架代码如下
+
+```python
+import cv2
+import numpy as np
+
+
+def close_op(img):
+    kernel = np.ones((5, 5), np.uint8)
+    img1 = cv2.dilate(img, kernel, iterations=1)
+    img2 = cv2.erode(img, kernel, iterations=1)
+    return img2
+
+
+def filter_green(img):
+    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
+    lower_green = np.array([50, 100, 50])
+    upper_green = np.array([70, 255, 255])
+    lower_red = np.array([0, 20, 100])
+    upper_red = np.array([10, 255, 255])
+
+    mask = cv2.inRange(hsv, lower_red, upper_red)
+    res = cv2.bitwise_and(img, img, mask=mask)
+    return close_op(res)
+
+
+if __name__ == '__main__':
+    imput_img = 'tower.jpeg'
+
+    ori = cv2.imread(imput_img)
+    image = cv2.imread(imput_img)
+
+    no_green = filter_green(image)
+
+    # TODO(You): 请在此实现 Harris 特征提取
+
+    images = np.concatenate((ori, no_green, image), axis=1)
+    cv2.imwrite('tower_harris.jpeg', images)
+    cv2.imshow('tower_harris', images)
+    cv2.waitKey()
+    cv2.destroyAllWindows()
+```
+
+以下正确实现通过 Harris 特征提取亭子瓦片角点的是？
+
+## 答案
+
+```python
+gray = cv2.cvtColor(no_green, cv2.COLOR_BGR2GRAY)
+gray = np.float32(gray)
+dst = cv2.cornerHarris(gray, 2, 3, 0.04)
+dst = cv2.dilate(dst, None)
+image[dst > 0.01*dst.max()] = [0, 0, 255]
+```
+
+## 选项
+
+### 没有取灰度图
+
+```python
+dst = cv2.cornerHarris(no_green, 2, 3, 0.04)
+dst = cv2.dilate(dst, None)
+image[dst > 0.01*dst.max()] = [0, 0, 255]
+```
+
+### 没有做膨胀处理
+
+```python
+gray = cv2.cvtColor(no_green, cv2.COLOR_BGR2GRAY)
+gray = np.float32(gray)
+dst = cv2.cornerHarris(gray, 2, 3, 0.04)
+image[dst > 0.01*dst.max()] = [0, 0, 255]
+```
+
+### 过滤掉代码不对
+
+```python
+gray = cv2.cvtColor(no_green, cv2.COLOR_BGR2GRAY)
+gray = np.float32(gray)
+dst = cv2.cornerHarris(gray, 2, 3, 0.04)
+dst = cv2.dilate(dst, None)
+image[lambda dst: dst > 0.01*dst.max()] = [0, 0, 255]
+```

data/1.OpenCV初阶/4.几何变换和图像特征/3.图像特征与特征提取/harris.py

+import cv2
+import numpy as np
+
+
+def close_op(img):
+    kernel = np.ones((5, 5), np.uint8)
+    img1 = cv2.dilate(img, kernel, iterations=1)
+    img2 = cv2.erode(img, kernel, iterations=1)
+    return img2
+
+
+def filter_green(img):
+    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
+    lower_green = np.array([50, 100, 50])
+    upper_green = np.array([70, 255, 255])
+    lower_red = np.array([0, 20, 100])
+    upper_red = np.array([10, 255, 255])
+
+    mask = cv2.inRange(hsv, lower_red, upper_red)
+    res = cv2.bitwise_and(img, img, mask=mask)
+    return close_op(res)
+
+
+if __name__ == '__main__':
+    imput_img = 'tower.jpeg'
+
+    ori = cv2.imread(imput_img)
+    image = cv2.imread(imput_img)
+
+    no_green = filter_green(image)
+    gray = cv2.cvtColor(no_green, cv2.COLOR_BGR2GRAY)
+    gray = np.float32(gray)
+
+    dst = cv2.cornerHarris(gray, 2, 3, 0.04)
+    dst = cv2.dilate(dst, None)
+
+    image[dst > 0.01*dst.max()] = [0, 0, 255]
+
+    images = np.concatenate((ori, no_green, image), axis=1)
+    # cv2.imwrite('tower_harris.jpeg', images)
+    cv2.imshow('tower_harris', images)
+    cv2.waitKey()
+    cv2.destroyAllWindows()