A two-stage automatic color thresholding technique
Thresholding is a prerequisite for many computer vision algorithms. By suppressing the background in an image, one can remove unnecessary information and shift one's focus to the object of inspection. We propose a two-stage histogram-based background suppression technique based on the chromatic...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Online Access: | https://hdl.handle.net/10356/171655 |
| _version_ | 1824456722264096768 |
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| author | Pootheri, Shamna Ellam, Daniel Grübl, Thomas Liu, Yang |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Pootheri, Shamna Ellam, Daniel Grübl, Thomas Liu, Yang |
| author_sort | Pootheri, Shamna |
| collection | NTU |
| description | Thresholding is a prerequisite for many computer vision algorithms. By suppressing the background in an image, one can remove unnecessary information and shift one's focus to the object of inspection. We propose a two-stage histogram-based background suppression technique based on the chromaticity of the image pixels. The method is unsupervised, fully automated, and does not need any training or ground-truth data. The performance of the proposed method was evaluated using a printed circuit assembly (PCA) board dataset and the University of Waterloo skin cancer dataset. Accurately performing background suppression in PCA boards facilitates the inspection of digital images with small objects of interest, such as text or microcontrollers on a PCA board. The segmentation of skin cancer lesions will help doctors to automate skin cancer detection. The results showed a clear and robust background-foreground separation across various sample images under different camera or lighting conditions, which the naked implementation of existing state-of-the-art thresholding methods could not achieve. |
| first_indexed | 2025-02-19T03:58:37Z |
| format | Journal Article |
| id | ntu-10356/171655 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:58:37Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1716552023-11-03T15:36:42Z A two-stage automatic color thresholding technique Pootheri, Shamna Ellam, Daniel Grübl, Thomas Liu, Yang School of Computer Science and Engineering HP-NTU Digital Manufacturing Corporate Lab Engineering::Computer science and engineering Image Binarization Robust Color Thresholding Thresholding is a prerequisite for many computer vision algorithms. By suppressing the background in an image, one can remove unnecessary information and shift one's focus to the object of inspection. We propose a two-stage histogram-based background suppression technique based on the chromaticity of the image pixels. The method is unsupervised, fully automated, and does not need any training or ground-truth data. The performance of the proposed method was evaluated using a printed circuit assembly (PCA) board dataset and the University of Waterloo skin cancer dataset. Accurately performing background suppression in PCA boards facilitates the inspection of digital images with small objects of interest, such as text or microcontrollers on a PCA board. The segmentation of skin cancer lesions will help doctors to automate skin cancer detection. The results showed a clear and robust background-foreground separation across various sample images under different camera or lighting conditions, which the naked implementation of existing state-of-the-art thresholding methods could not achieve. Nanyang Technological University Published version This study is supported under the RIE2020 Industry Alignment Fund—Industry Collaboration Projects (IAF-ICP) Funding Initiative (I1801E0028), as well as cash and in-kind contribution from the industry partner, HP Inc., through the HP-NTU Digital Manufacturing Corporate Lab. 2023-11-02T07:29:40Z 2023-11-02T07:29:40Z 2023 Journal Article Pootheri, S., Ellam, D., Grübl, T. & Liu, Y. (2023). A two-stage automatic color thresholding technique. Sensors, 23(6), 3361-. https://dx.doi.org/10.3390/s23063361 1424-8220 https://hdl.handle.net/10356/171655 10.3390/s23063361 36992072 2-s2.0-85151177041 6 23 3361 en IAF-ICP Sensors © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). application/pdf |
| spellingShingle | Engineering::Computer science and engineering Image Binarization Robust Color Thresholding Pootheri, Shamna Ellam, Daniel Grübl, Thomas Liu, Yang A two-stage automatic color thresholding technique |
| title | A two-stage automatic color thresholding technique |
| title_full | A two-stage automatic color thresholding technique |
| title_fullStr | A two-stage automatic color thresholding technique |
| title_full_unstemmed | A two-stage automatic color thresholding technique |
| title_short | A two-stage automatic color thresholding technique |
| title_sort | two stage automatic color thresholding technique |
| topic | Engineering::Computer science and engineering Image Binarization Robust Color Thresholding |
| url | https://hdl.handle.net/10356/171655 |
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