/inner-boundary-tracing

Primary LanguageJupyter Notebook

Computer vision algorithms

1. boundary tracing algorithm:

The border tracing algorithm is used to extract the contours of the objects (regions) from an image. When applying this algorithm it is assumed that the image with regions is either binary or those regions have been previously labeled.

Algorithm's steps:

1. Search the image from top left until a pixel of a new region is found; this pixel Po

is the starting pixel of the region border. Define a variable dir which stores the direction of the previous move along the border from the previous border element to the current border element.

Assign :

(a) dir = 0 if the border is detected in 4-connectivity

(b) dir = 7 if the border is detected in 8-connectivity

2. Search the 3x3 neighborhood of the current pixel in an anti-clockwise direction,

beginning the neighborhood search at the pixel positioned in the direction

(a) (dir + 3) mod 4

(b) (dir + 7) mod 8 if dir is even or (dir + 6) mod 8 if dir is odd

The first pixel found with the same value as the current pixel is a new boundary element Pn. Update the dir value.

3. If the current boundary element Pn is equal to the second border element P1 and if

the previous border element Pn-1 is equal to Po, stop. Otherwise repeat step (2).

4. The detected border is represented by pixels Po ... Pn-2.

5. after detecting the first object, it's removed from the original image , then the algorithm starts again with the image after removing the object , and detects the boundary for the next object , then we delete it from the original image , and so on so forth.

5.1 Uploading an existing image using BoundaryTracing_2.py

image

# Installing Dependencies
pip install numpy as np
pip install opencv-python

# clone the rebo

# Running the application 
python3 boundaryTracing.py

2. Hough transform :

The circle Hough Transform (CHT) is a basic feature extraction technique used in digital image processing for detecting circles in imperfect images. The circle candidates are produced by “voting” in the Hough parameter space and then selecting local maxima in an accumulator matrix.