期刊
CARBOHYDRATE POLYMERS
卷 255, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.carbpol.2020.117372
关键词
Gelatinization; Computer vision; Quantification; Canny detection; Mathematical morphology
资金
- National Key R&D Program of China [2018YFD0400701]
- Guangdong Province Key Area RD program [2019B020210002]
- 111 project [B17018]
- National Science Foundation of China [61571005]
- International cooperation project of Guangzhou Development Zone [2018GH18]
- National Undergraduate Training Program for Innovation and Entrepreneurship of SCUT
A novel image segmentation methodology combined with optical microscopy observation was developed for qualifying starch swelling. Starch granules in the micrograph were successfully segmented based on high-precision edges extraction achieved by Canny edge detection together with mathematical morphology operation. Granules were automatically identified by computer vision and characterized by giving quantifiable area of these granules.
A novel image segmentation methodology combined with optical microscopy observation was developed for qualifying starch swelling. Starch granules in the micrograph were successfully segmented based on high-precision edges extraction achieved by Canny edge detection together with mathematical morphology operation. Granules were automatically identified by computer vision and characterized by giving quantifiable area of these granules. The evolved swelling process could be generally divided into two phases. During the first phase, starch granules were only swollen up by 2.56 %, which is hard to be identified by conventional naked eye. During the following narrow temperature interval (60-66 degrees C), these starch granules were detected to swell up significantly by 9.08 %. Through the granule area variable, swelling capacity was high-throughput characterized, which allows for the whole evaluation to be completed within a couple of minutes. The proposed methodology showed a high accuracy and potential as a novel technique for characterizing gelatinization.
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