Segmenting License Plate Characters
I am facing a problem in segmenting characters from a license plate image.
I have applied following method to extract license plate characters”
I am facing a problem in segmenting characters from a license plate image.
I have applied following method to extract license plate characters”
The following picture will tell you what I want.
I have a large number of images of a fixed size (say 500*500). I want to write a python script which will resize them to a fixed size (say 800*800) but will keep the original image at the center and fill the excess area with a fixed color (say black).
I’m writing an opencv program and I found a script on another stackoverflow question: Computer Vision: Masking a human hand
I’m looking for a way to find the most dominant color/tone in an image using python. Either the average shade or the most common out of RGB will do. I’ve looked at the Python Imaging library, and could not find anything relating to what I was looking for in their manual, and also briefly at VTK.
I’ve been trying for the last few days to get a sudoku grid from a picture, and I have been struggling on getting the smaller squares of the grid.
I am working on the picture below. I thought processing the image with a canny filter would work fine, but it didn’t and I couldn’t get every contour of each square. I then put adaptive threshold, otsu, and a classic thresholding to the test, but every time, it just could not seem to capture every small square.
When photographing a sheet of paper (e.g. with phone camera), I get the following result (left image) (jpg download here). The desired result (processed manually with an image editing software) is on the right:
I am trying to extract red color from an image. I have code that applies threshold to leave only values from specified range: