python - 如何在Open CV Python中消除这些噪音？

Question

嗨，我想发生的是消除噪音，只认出圆圈。到目前为止，我有以下代码:

import cv2
import numpy as np
import math

cap = cv2.VideoCapture(0)

while True:
    try:
        ret, frame = cap.read()
        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) #convert from bgr to 
hsv color space

        lower = np.array([0,0,255])
        upper = np.array([255, 255, 255])

        mask = cv2.inRange(hsv, lower, upper) 

        im2, contours, hierarchy = 
cv2.findContours(mask,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)
        area = sorted(contours, key=cv2.contourArea, reverse=True)
        contour = area[0]
        (x,y),radius = cv2.minEnclosingCircle(contour)
        radius = int(radius)
        area = cv2.contourArea(contour)
        circ = 4*area/(math.pi*(radius*2)**2)
        print(circ)
    except:
        pass

    cv2.imshow('mask', mask)
    cv2.imshow('frame', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

它的作用是检测最亮的光线并检查其圆度。我想发生的是消除噪音并仅检测到圆圈。希望您能对我的代码有所帮助。

这只是我的程序检测到最亮像素的一个示例。这是原始图片:

Answer 1

您可以尝试通过过滤尺寸范围以外的其他轮廓来选择轮廓。您应该了解，我也刚刚开始学习python和opencv，并且可能有很多更好的方法。代码应该是这样的:

import cv2
import numpy as np
import math

cap = cv2.VideoCapture(0)

while True:
    try:
        ret, frame = cap.read()
        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) #convert from bgr to 

        lower = np.array([0,0,255])
        upper = np.array([255, 255, 255])

        mask = cv2.inRange(hsv, lower, upper) 

        im2, contours, hierarchy = cv2.findContours(mask,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)
        area = sorted(contours, key=cv2.contourArea, reverse=True)
        for number in range(0, len(area)):
            cnts = area[number]
            if 40 < len(cnts) < 80:
                contour = area[number]
                break
        (x,y),radius = cv2.minEnclosingCircle(contour)
        radius = int(radius)
        area2 = cv2.contourArea(contour)
        circ = 4*area2/(math.pi*(radius*2)**2)
        print(circ)
    except:
        pass

    cv2.imshow('mask', mask)
    cv2.imshow('frame', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

U必须更改for循环的范围，使其适合您的目的。

更新:

甚至更好... u可以消除其他轮廓(带有圆形准则的噪声):

import cv2
import numpy as np
import math

cap = cv2.VideoCapture(0)

while True:
    try:
        ret, frame = cap.read()
        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) #convert from bgr to 

        lower = np.array([0,0,255])
        upper = np.array([255, 255, 255])

        mask = cv2.inRange(hsv, lower, upper) 

        im2, contours, hierarchy = cv2.findContours(mask,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)
        area = sorted(contours, key=cv2.contourArea, reverse=True)
        for number in range(0, len(area)):
            cnts = area[number]
            if 40 < len(cnts) < 80:
                contour = area[number]
                (x,y),radius = cv2.minEnclosingCircle(contour)
                radius = int(radius)
                area2 = cv2.contourArea(contour)
                circ = 4*area2/(math.pi*(radius*2)**2)
                if 0.8 < circ < 1.5:
                    rect = cv2.boundingRect(contour)
                    x,y,w,h = rect
                    cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2)
                    cv2.putText(frame,'Laser point detected',(x+w+10,y+h),0,0.5,(0,255,0))
                    print(circ)
                    break       
    except:
        pass

    cv2.imshow('mask', mask)
    cv2.imshow('frame', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break