This git repository provides an adaptive barcode detection and decoding function for robust barcode detection and decoding. The project is a part of expert in team inovation project (E22). The code along with an example are provided at https://github.com/Arthicha/Barcode_Detection_and_Decoding.git.
The flowchart of the provided example program is presented in the figure below. The "adaptive barcode detection and decoding" block denotes the "adaptive_read()" function imported from "barcode_reader.py".
To install the required python modules (standard modules, such as numpy and opencv, not included), run pip install -r requirement.txt.
To run an example code, please run python example.py. The example program will perform adaptive barcode detection and decoding on all images locating in the "imgs" folder.
To view the readme, please run grip -b readme.md.
from barcode_reader import *
img = <input image>
code, intermediate_imgs = adaptive_read(img, imgsize=(<width>,<height>), detectionparams=(<k>,<dk>,<kmax>), binarizationparams=(<th>,<dth>,<thmax>))
File: barcode_reader.py
Description: perform adaptive barcode detection and decoding
Input:
- img (opencv array): an image of an arbitrary size
- imgsize (tuple (w,h)): the desired size (width,height)
- detectionparams (tuple (k,dk,kmax)): the adaptive detection parameters
- k (int): initial morphological transformation kirnel size
- dk (int): morphological transformation kirnel step size
- kmax (int): maximum morphological transformation kirnel step size
- binarizationparams (tuble (th,dth,thmax)): adaptive binarization parameters
- th (int): initial threshold
- dth (int): threshold step
- thmax (int): maximum threshold
Output:
- code (string): barcode data
- intermidiate_imgs (list of images): intermediate images
test1.jpg
test2.jpg
test3.jpg
test4.jpg
test5.jpg
test6.jpg
test7.jpg
test8.jpg
test9.jpg
This code is modified from this git repository.