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 chromaticity o...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/6/3361 |
| _version_ | 1797608976129458176 |
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| author | Shamna Pootheri Daniel Ellam Thomas Grübl Yang Liu |
| author_facet | Shamna Pootheri Daniel Ellam Thomas Grübl Yang Liu |
| author_sort | Shamna Pootheri |
| collection | DOAJ |
| 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 | 2024-03-11T05:55:11Z |
| format | Article |
| id | doaj.art-441eff32beaf4b7a8e67a6a3ade9ffb6 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T05:55:11Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-441eff32beaf4b7a8e67a6a3ade9ffb62023-11-17T13:49:37ZengMDPI AGSensors1424-82202023-03-01236336110.3390/s23063361A Two-Stage Automatic Color Thresholding TechniqueShamna Pootheri0Daniel Ellam1Thomas Grübl2Yang Liu3HP-NTU Digital Manufacturing Corporate Lab, Nanyang Technological University, Singapore 639798, SingaporeHP Security Lab, HP Inc., Bristol BS1 6NP, UKHP-NTU Digital Manufacturing Corporate Lab, Nanyang Technological University, Singapore 639798, SingaporeHP-NTU Digital Manufacturing Corporate Lab, Nanyang Technological University, Singapore 639798, SingaporeThresholding 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.https://www.mdpi.com/1424-8220/23/6/3361image binarizationrobust color thresholdingimage segmentationhistogram analysisprinted circuit assembly board inspectionmedical image analysis |
| spellingShingle | Shamna Pootheri Daniel Ellam Thomas Grübl Yang Liu A Two-Stage Automatic Color Thresholding Technique Sensors image binarization robust color thresholding image segmentation histogram analysis printed circuit assembly board inspection medical image analysis |
| 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 | image binarization robust color thresholding image segmentation histogram analysis printed circuit assembly board inspection medical image analysis |
| url | https://www.mdpi.com/1424-8220/23/6/3361 |
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