Opencv模板匹配

1 理论

  模板匹配是一种用于在目标图像中搜索给定模板位置的方法。对此，Opencv中带有函数cv.matchTemplate()，其将模板在目标图像上滑动，然后在模板图像下比较模板和输入图像的拼盘。返回对象为一个灰度图像，每个像素表示该像素的邻域与模板的匹配程度。
  令$W\times H$表示目标图像的大小，$w\times h$表示模板大小，则输出图像的大小为$(W-w+1)\times (H-h+1)$。之后，可以使用**cv.minMaxLoc()**查看最大最小值。

2 测试图像

2.1 单对象

  1）目标图像：

  2）模板

2.2 多对象

  1）目标图像：

  2）模板：

3 单对象的模板匹配

import cv2 as cv
import matplotlib.pyplot as plt
import warnings

warnings.filterwarnings("ignore")


def get_match_template(
        target_path: str,
        template_path: str,
        methods: list = None
):
    if methods is None:
        methods = ['cv.TM_CCOEFF', 'cv.TM_CCOEFF_NORMED', 'cv.TM_CCORR',
                   'cv.TM_CCORR_NORMED', 'cv.TM_SQDIFF', 'cv.TM_SQDIFF_NORMED']

    target = cv.imread(target_path, 0)
    target_copy = target.copy()
    template = cv.imread(template_path, 0)

    w, h = template.shape[::-1]
    for meth in methods:
        method = eval(meth)
        target = target_copy.copy()

        res = cv.matchTemplate(target, template, method)
        min_val, max_val, min_loc, max_loc = cv.minMaxLoc(res)
        if method in [cv.TM_SQDIFF, cv.TM_SQDIFF_NORMED]:
            top_left = min_loc
        else:
            top_left = max_loc
        bottom_right = (top_left[0] + w, top_left[1] + h)
        cv.rectangle(target, top_left, bottom_right, 255, 2)
        plt.subplot(121), plt.imshow(res, 'gray')
        plt.title('Matching Result'), plt.xticks([]), plt.yticks([])
        plt.subplot(122), plt.imshow(target, 'gray')
        plt.title('Detected Point'), plt.xticks([]), plt.yticks([])
        plt.suptitle(meth)
        plt.show()


def test_get_match_template(
):
    target_path = "haizeiwang.png"
    template_path = "moban.png"
    get_match_template(target_path, template_path)


if __name__ == '__main__':
    test_get_match_template()

  输出如下：

4 多对象的模板匹配

import cv2 as cv
import numpy as np
import warnings

warnings.filterwarnings("ignore")


def get_match_template(
        target_path: str,
        template_path: str,
        threshold: float = 0.65
):

    target = cv.imread(target_path)
    target_gray = cv.cvtColor(target, cv.COLOR_BGR2GRAY)
    template = cv.imread(template_path, 0)
    w, h = template.shape[::-1]
    res = cv.matchTemplate(target_gray, template, cv.TM_CCOEFF_NORMED)

    loc = np.where(res >= threshold)
    for pt in zip(*loc[::-1]):
        cv.rectangle(target, pt, (pt[0] + w, pt[1] + h), (0, 0, 255), 2)
    cv.imshow("", target)
    cv.waitKey()


def test_get_match_template(
):
    target_path = "xiaoxiaole.png"
    template_path = "green.png"
    get_match_template(target_path, template_path)


if __name__ == '__main__':
    test_get_match_template()

  输出如下：

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参考文献：
【1】Opencv中文文档。