[Updated The Question at the End] I'm trying to detect a design pattern of simple geometrical shapes in a 640x480 image. I have divided the image in 32x32 blocks and checking in which block each shape's center lies.
Based on this calculation I created a numpy matrix of (160x120) zeros (float32) with
col=640/4
row=480/4
Each time a shape is found, the center is calculated and check in which block it is found. The corresponding item along with its 8 neighbors in 160x120 numpy array are set to 1. In the end the 160x120 numpy array is represented as a grayscale image with black background and white pixels representing the blocks of detected shapes.
As shown in the image below.
The image in top left corner represents the 160x120 numpy array. No issue so far.
As you can see the newly generated image has a white line on black foreground. I want to find the rho,theta,x0,y0,x1,y1 for this line. So I decided to use HoughLines transformation for this.
For is as followed:
edges = cv2.Canny(np.uint8(g_quadrants), 50, 150, apertureSize=3)
lines = cv2.HoughLines(edges, 1, np.pi / 180, 200)
print lines
Here g_quadrants is the 160x120 matrix representing a gray scale image but output of cv2.HoughLines does not contain anything but None.
Please help me with this.
Update:
The small window with a black and white (np.float32 consider GrayScale) image displaying a white is what I get actually when I
- Divide the 640x480 in 32x32 blocks
- Find the triangles in the image
- Create a 32x32 matrix to map the results for each block
- Update the corresponding matrix element by 1 if a triangle is found in a block
Zoomed View:
You can see there are white pixels forming a straight line. The may be some unwanted detected. I need to eliminate unwanted lone pixels and reconstructing a continuous straight line. That may be achieved by dilating then eroding the image. I need the find x0,y0, x1,y1, rho, theta of this line.
Their may be more than one lines. In that case I need to find top 2 lines with respect to length.