How could i improve my opencv program to detect only the crosswalk?-CodePudding

I would like to detect the pedestrian crossing in the image below, and fill it with red color, but the program detect other things too. Here is my code:

import cv2
import numpy as np

img = cv2.imread("zebra_lane.jpg")
cv2.imshow("kep" ,img)
imgContour=img.copy()

def getContours(img, imgContour):
    contours, hierarchy = cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)

    for cnt in contours:
        area=cv2.contourArea(cnt)
        if area>500:
            cv2.drawContours(imgContour, contours, -1, (0, 0, 255), 2)

            # peri=cv2.arcLength(cnt,True)
            # approx = cv2.approxPolyDP(cnt,0.02*peri,True)
            # # print(len(approx))
            # if len(approx)==4:
            #     x,y,w,h =cv2.boundingRect(approx)
            #     cv2.rectangle(imgContour,(x,y),(x w,y h), (0,0,255),1)


imgblur=cv2.GaussianBlur(img,(7,7),1)
imggray=cv2.cvtColor(imgblur,cv2.COLOR_BGR2GRAY)


imgcanny=cv2.Canny(imggray,150,90)
cv2.imshow("kep" ,imgcanny)

kernel=np.ones((1,1))
imgDil = cv2.dilate(imgcanny,kernel,iterations=1)
cv2.imshow("kep" ,imgDil)


getContours(imgDil,imgContour)
cv2.imshow("contour",imgContour)

CodePudding user response：

Here is one way to do that in Python/OpenCV.

Read the input
Threshold on the white/gray sidewalk stripes
Apply morphology open and close
Get external contours
Filter contours on area and keep good contours
Draw good contours on input
Combine contours
Compute convex hull of combined contours
Draw convex hull on input
Save results

Input:

import cv2
import numpy as np

# read image
img = cv2.imread('walkway.jpg')

# threshold on white/gray sidewalk stripes
lower = (100,130,130)
upper = (180,200,200)
thresh = cv2.inRange(img, lower, upper)


# apply morphology close to fill interior regions in mask
kernel = np.ones((3,3), np.uint8)
morph = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)
kernel = np.ones((5,5), np.uint8)
morph = cv2.morphologyEx(morph, cv2.MORPH_CLOSE, kernel)

# get contours
cntrs = cv2.findContours(morph, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cntrs = cntrs[0] if len(cntrs) == 2 else cntrs[1]

# filter on area
contours = img.copy()
good_contours = []
for c in cntrs:
    area = cv2.contourArea(c)
    if area > 200:
        cv2.drawContours(contours, [c], -1, (0,0,255), 1)
        good_contours.append(c)

# combine good contours
contours_combined = np.vstack(good_contours)

# get convex hull
result = img.copy()
hull = cv2.convexHull(contours_combined)
cv2.polylines(result, [hull], True, (0,0,255), 2)

# write result to disk
cv2.imwrite("walkway_thresh.jpg", thresh)
cv2.imwrite("walkway_morph.jpg", morph)
cv2.imwrite("walkway_contours.jpg", contours)
cv2.imwrite("walkway_result.jpg", result)

# display it
cv2.imshow("THRESH", thresh)
cv2.imshow("MORPH", morph)
cv2.imshow("CONTOURS", contours)
cv2.imshow("RESULT", result)
cv2.waitKey(0)

Threshold image:

Morphology image:

Contour image:

Result: