Chapter title |
A Printer Indexing System for Color Calibration with Applications in Dietary Assessment
|
---|---|
Chapter number | 44 |
Book title |
New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops
|
Published in |
Lecture notes in computer science, August 2015
|
DOI | 10.1007/978-3-319-23222-5_44 |
Pubmed ID | |
Book ISBNs |
978-3-31-923221-8, 978-3-31-923222-5
|
Authors |
Fang, Shaobo, Liu, Chang, Zhu, Fengqing, Boushey, Carol, Delp, Edward, Shaobo Fang, Chang Liu, Fengqing Zhu, Carol Boushey, Edward Delp |
Abstract |
In image based dietary assessment, color is a very important feature in food identification. One issue with using color in image analysis in the calibration of the color imaging capture system. In this paper we propose an indexing system for color camera calibration using printed color checkerboards also known as fiducial markers (FMs). To use the FM for color calibration one must know which printer was used to print the FM so that the correct color calibration matrix can be used for calibration. We have designed a printer indexing scheme that allows one to determine which printer was used to print the FM based on a unique arrangement of color squares and binarized marks (used for error control) printed on the FM. Using normalized cross correlation and pattern detection, the index corresponding to the printer for a particular FM can be determined. Our experimental results show this scheme is robust against most types of lighting conditions. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 10 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Other | 2 | 20% |
Student > Doctoral Student | 2 | 20% |
Student > Ph. D. Student | 2 | 20% |
Student > Bachelor | 1 | 10% |
Professor | 1 | 10% |
Other | 1 | 10% |
Unknown | 1 | 10% |
Readers by discipline | Count | As % |
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Computer Science | 3 | 30% |
Agricultural and Biological Sciences | 1 | 10% |
Medicine and Dentistry | 1 | 10% |
Neuroscience | 1 | 10% |
Engineering | 1 | 10% |
Other | 0 | 0% |
Unknown | 3 | 30% |