How to find the center and angle of objects in an image?

Question

I am using python and OpenCV. I am trying to find the center and angle of the batteries:

Image of batteries with random angles:

The code than I have is this:

import cv2
import numpy as np


img = cv2.imread('image/baterias2.png')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
img2 = cv2.imread('image/baterias4.png',0)


minLineLength = 300
maxLineGap = 5

edges = cv2.Canny(img2,50,200)
cv2.imshow('Canny',edges)
lines = cv2.HoughLinesP(edges,1,np.pi/180,80,minLineLength,maxLineGap)
print lines
salida = np.zeros((img.shape[0],img.shape[1]))
for x in range(0, len(lines)):
    for x1,y1,x2,y2 in lines[x]:
        cv2.line(salida,(x1,y1),(x2,y2),(125,125,125),0)#  rgb


cv2.imshow('final',salida)
cv2.imwrite('result/hough.jpg',img)
cv2.waitKey(0)

Any ideas to work it out?

Answer 1

Almost identical to one of my other answers. PCA seems to work fine.

import cv2
import numpy as np

img = cv2.imread("test_images/battery001.png")  #load an image of a single battery
img_gs = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)  #convert to grayscale

#inverted binary threshold: 1 for the battery, 0 for the background
_, thresh = cv2.threshold(img_gs, 250, 1, cv2.THRESH_BINARY_INV)

#From a matrix of pixels to a matrix of coordinates of non-black points.
#(note: mind the col/row order, pixels are accessed as [row, col]
#but when we draw, it's (x, y), so have to swap here or there)
mat = np.argwhere(thresh != 0)

#let's swap here... (e. g. [[row, col], ...] to [[col, row], ...])
mat[:, [0, 1]] = mat[:, [1, 0]]
#or we could've swapped at the end, when drawing
#(e. g. center[0], center[1] = center[1], center[0], same for endpoint1 and endpoint2),
#probably better performance-wise


mat = np.array(mat).astype(np.float32) #have to convert type for PCA

#mean (e. g. the geometrical center) 
#and eigenvectors (e. g. directions of principal components)
m, e = cv2.PCACompute(mat, mean = np.array([]))

#now to draw: let's scale our primary axis by 100, 
#and the secondary by 50

center = tuple(m[0])
endpoint1 = tuple(m[0] + e[0]*100)
endpoint2 = tuple(m[0] + e[1]*50)

red_color = (0, 0, 255)
cv2.circle(img, center, 5, red_color)
cv2.line(img, center, endpoint1, red_color)
cv2.line(img, center, endpoint2, red_color)
cv2.imwrite("out.png", img)

Answer 2

• To find out the center of an object, you can use the Moments. Threshold the image and get the contours of the object with findContours. Compute the Moments withcv.Moments(arr, binary=0) → moments. As arr you can pass the contours. Then the coordinates of the center are computed as x = m10/m00 and y = m01/m00.

• To get the orientation, you can draw a minimum Rectangle around the object and compute the angle between the longer side of the rectangle and a vertical line.

Answer 3

You can reference the code.

import cv2
import imutils
import numpy as np

PIC_PATH = r"E:\temp\Battery.jpg"    

image = cv2.imread(PIC_PATH)

gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)    

edged = cv2.Canny(gray, 100, 220)

kernel = np.ones((5,5),np.uint8)
closed = cv2.morphologyEx(edged, cv2.MORPH_CLOSE, kernel)

cnts = cv2.findContours(closed.copy(), cv2.RETR_EXTERNAL,
    cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if imutils.is_cv2() else cnts[1]

cv2.drawContours(image, cnts, -1, (0, 255, 0), 4)

cv2.imshow("Output", image)
cv2.waitKey(0)

The result picture is,