Automatic Wood Pith Detection: Local Orientation Estimation and Robust Accumulation

ICPR 2024 | Arxiv | Slides

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Pith detection at the right image (blue dot)

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Installation

conda create --name pith python=3.11
conda activate pith
conda install -n pith pip

pip install .

Dataset

python fetch_dataset.py

Examples of usage

Import the module

from automatic_wood_pith_detector.automatic_wood_pith_detector import  apd, apd_pcl, apd_dl
import cv2 

st_sigma = 1.2
st_w = 3
lo_w = 11
percent_lo = 0.5

img_in= cv2.imread('./Input/F02c.png')
peak = apd(img_in, st_sigma, st_w, lo_w, rf = 7, percent_lo = percent_lo, max_iter = 11, epsilon =10 ** -3)

CLI

Example of usage:

python main.py --filename ./Input/F02c.png --output_dir Output/ --new_shape 640 --debug 1

Example of usage with pclines postprocessing

python main.py --filename ./Input/F02b.png --output_dir Output/ --new_shape 640 --debug 1 --method 1

Example of usage with apd-dl

python main.py --filename ./Input/F02b.png --output_dir Output/ --new_shape 640 --debug 1 --method 2

Citation

If you use this code, please cite the following paper:

@InProceedings{marichal2024automatic,
author="Marichal, Henry and Passarella, Diego and Randall, Gregory",
editor="Antonacopoulos, Apostolos and Chaudhuri, Subhasis and Chellappa, Rama and Liu, Cheng-Lin and Bhattacharya, Saumik and Pal, Umapada",
title="Automatic Wood Pith Detector: Local Orientation Estimation and Robust Accumulation",
booktitle="Pattern Recognition",
year="2025",
publisher="Springer Nature Switzerland",
address="Cham",
pages="1--15",
isbn="978-3-031-78447-7"
}

License

License for th source code: MIT