如何使用 python opencv 可靠地仅选择 maksed 液滴图像的外轮廓？

Question

我正在编写一个程序，它需要检测液滴的外轮廓并将椭圆拟合到该形状。

我有一个运行良好的设置：

canny 边缘检测
找到等高线
选择最长的轮廓
拟合椭圆

但现在该过程需要包括用于分配液滴的注射器的面罩，它将外轮廓分成两半。我知道如何屏蔽从 canny 返回的数组中检测到的边缘，但我不知道如何从那里继续。

我需要使用两个外部轮廓来拟合椭圆，但我不知道如何可靠地提取它们。

最小工作代码：

from typing import Tuple
import cv2
import numpy as np

def evaluate_droplet(img, y_base, mask: Tuple[int,int,int,int] = None):
    # crop img from baseline down (contains no useful information)
    crop_img = img[:y_base,:]
    shape = img.shape
    height = shape[0]
    width = shape[1]
    # calculate thrresholds
    thresh_high, thresh_im = cv2.threshold(img, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
    thresh_low = 0.5*thresh_high
    bw_edges = cv2.Canny(crop_img, thresh_low, thresh_high)
    
    # block detection of syringe
    if (not mask is None):
        x,y,w,h = mask
        bw_edges[y:y+h, x:x+w] = 0
        cv2.imshow('bw',bw_edges)
        cv2.waitKey(0)


# for testing purposes:
if __name__ == "__main__":
    im = cv2.imread('untitled1.png', cv2.IMREAD_GRAYSCALE)
    im = np.reshape(im, im.shape + (1,) )
    (h,w,d) = np.shape(im)
    try:
        drp = evaluate_droplet(im, 250, (int(w/2-40), 0, 80, h))
    except Exception as ex:
        print(ex)
    cv2.imshow('Test',im)
    cv2.waitKey(0)

使用的图像：

Answer 1

我暂时这样解决了：

计算每个轮廓的边界矩形的面积并选择最大的两个

def evaluate_droplet(img, y_base, mask: Tuple[int,int,int,int] = None):
    # crop img from baseline down (contains no useful information)
    crop_img = img[:y_base,:]
    shape = img.shape
    height = shape[0]
    width = shape[1]
    # calculate thrresholds
    thresh_high, thresh_im = cv2.threshold(img, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
    thresh_low = 0.5*thresh_high
    bw_edges = cv2.Canny(crop_img, thresh_low, thresh_high)
    
    # block detection of syringe
    if (not mask is None):
        x,y,w,h = mask
        bw_edges[y:y+h, x:x+w] = 0

    contours, hierarchy = cv2.findContours(bw_edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
    if len(contours) == 0:
        print("no contour found!")

    cont_area_list = []
    # match contours with their bounding rect area
    for cont in contours:
        x,y,w,h = cv2.boundingRect(cont)
        cont_area_list.append((cont, w*h))
    
    # sort combined list by area
    cont_areas_sorted = sorted(cont_area_list, key=lambda item: item[1])

    # largest 2 contours, assumes mask splits largest contour in the middle
    if not mask is None:
        largest_conts = [elem[0] for elem in cont_areas_sorted[-2:]]
        # merge largest 2 contorus into one for handling purposes
        contour = np.concatenate((largest_conts[0], largest_conts[1]))
    # if no mask is used use only single largest contour
    else:
        contour = cont_areas_sorted[-1][0]
    
    # display bounding rect of final contour
    x,y,w,h = cv2.boundingRect(contour)
    bw_edges = cv2.rectangle(bw_edges, (x,y), (x+w,y+h), (255,255,255))
    cv2.imshow('bw',bw_edges)
    cv2.waitKey(0)

如何使用 python opencv 可靠地仅选择 maksed 液滴图像的外轮廓？

How can I reliably choose only the outer contour of a maksed droplet image with python opencv?

python

opencv

opencv-python