Characterization of shapes for use in classification of starch grains images

Microscopy Research and Technique

Volumn 71, Issue 9, 2008, Pages 651-658

  Tong, Chong Sze ^a   Choy, Siu Kai ^a   Chiu, Sung Nok ^a   Zhao, Zhong Zhen ^a   Liang, Zhi Tao ^a  

^a HONG KONG BAPTIST UNIVERSITY   (Hong Kong)

Author keywords

Chinese materia medica; Chord length distribution; Granulometry; Microscopic classification; Noise filtering; Similarity measurement; Starch grains

Indexed keywords

MEDICAL APPLICATIONS; PLANT EXTRACTS;

CHINESE HERBAL MEDICINES; CHINESE MATERIA MEDICA; CHORD LENGTH DISTRIBUTION; DENOISING FILTERS; GRANULOMETRIES; MICROSCOPIC CLASSIFICATION; NOISE FILTERING; SIMILARITY MEASUREMENTS; STARCH GRAIN;

STARCH;

MATERIA MEDICA; STARCH;

ARTICLE; BIOLOGY; EXPERIMENTAL STUDY; FILTER; GRAIN; IMAGE ANALYSIS; MICROSCOPY; MORPHOLOGY; NONHUMAN; PRIORITY JOURNAL;

EID: 53049099592     PISSN: 1059910X     EISSN: 10970029     Source Type: Journal    
DOI: 10.1002/jemt.20606     Document Type: Article

References (19)

1. British Herbal Medicine Association. 1996. British Herbal Medicine Pharmacopoeia. London: Biddles, 212 p.
2. Chang T, Kuo CCJ. 1993. Texture analysis and classification with tree-structured wavelet transform. IEEE Trans Image Process 2:429-441.
3. Choy SK, Tong CS. 2006. Supervised learning using characteristic generalized gaussian density and its application to chinese materia medica identification. Wavelet analysis and applications. Applied and numerical harmonic analysis series. Birkhauser: Verlag. pp. 443-452.
4. Health Ministry of Central People's Government. 1953. Pharmacopoeia of the People's Republic of China. Beijing: The Commercial Press, 381 p.
5. Kang TG. 2003. Microscopic identification of Chinese material medicia. Shanghai: China Press of Traditional Chinese Medicine. 623 p.
6. Laine A, Fan J. 1993. Texture classification by wavelet packet signatures. IEEE Trans Pattern Anal Mach Intell 15:1186-1191.
7. Li F, Shen C, Pi L. 2006. A new diffusion-based variational model for image denoising and segmentation. J Math Imaging Vis 26:115-125.
8. Liu X, Wang D. 2003. Texture classification using spectral histograms. IEEE Trans Image Process 12:661-670.
9. Matheron, G. 1975. Random sets and integral geometry. New York: Wiley.
10. Ministry of Health and Family Welfare of South Korea. 2002. Korea Herbal Pharmacopoeia. 505 p.
11. Serra J. 1982. Image analysis and mathematical morphology. London: Academic Press.
12. Smith SP, Jain AK. 1982. Chord distribution for shape matching, computer graphics and image processing 20:259-271.
13. Society of Japanese Pharmacopoeia. 2001. Japanese Pharmacopoeia (English version), 14th ed. Tokyo: Junkudo Book Shop. 1325 p.
14. Stoyan D, Kendall WS, Mecke J. 1995. Stochastic geometry and its applications, 2nd ed. Chichester: Wiley.
15. The Pharmacopoeia Committee of the Ministry of Health of the People's Republic of China. 1963. Pharmacopoeia of the People's Republic of China, Vol. I. Beijing: People's Heath Publishing House, 407 p.
16. Tong CS, Choy SK. 2003. Classification of Chinese herbal medicine using microscopic image processing. Bernoulli Society East Asian and Pacific Regional Conference. The Hong Kong University of Science and Technology. p 74.
17. Tong CS, Choy SK, Zhao ZZ, Liang ZT, Chen HB. 2007. Identification of starch grains in microscopic images based on granulometric operations. Microsc Res Tech 70:724-732.
18. You Z, Jain AK. 1984. Performance evaluation of shape matching via chord length distribution. Computer vision, graphics and image processing. Amsterdam: Elsevier, Vol. 28. pp. 185-198.
19. Zhang WJ. 2001. Pharmacognostic study of Arctium tomentosum mill and microscopic study of Chinese materia medica. Master of Medicine Thesis. Liaoning, Shenyang, China: Liaoning College of Traditional Chinese Medicine.