Content-based image retrieval: A new promising technique in powder technology

Pharmaceutical Development and Technology

Volumn 5, Issue 2, 2000, Pages 171-179

  Laitinen, Niklas ^a   Antikainen, Osmo ^a   Mannermaa, Jukka Pekka ^a   Yliruusi, Jouko ^a  

^a UNIVERSITY OF HELSINKI   (Finland)

Author keywords

Content based image retrieval; Feature extraction; Image information; Image similarity; Powder technology

Indexed keywords

MICROCRYSTALLINE CELLULOSE;

ALGORITHM; ARTICLE; DRUG MIXTURE; EXTRACTION; IMAGE ANALYSIS; INFORMATION RETRIEVAL; PARTICLE SIZE; POWDER; PRIORITY JOURNAL; TECHNOLOGY;

CELLULOSE; DRUG COMPOUNDING; IMAGE PROCESSING, COMPUTER-ASSISTED; LASERS; PARTICLE SIZE; POWDERS;

EID: 0034112020     PISSN: 10837450     EISSN: None     Source Type: Journal    
DOI: 10.1081/PDT-100100532     Document Type: Article

References (26)

1. F. M. Ezler and M. S. Sanderson, Particle size analysis: a comparative study of various methods, Part. Part. Syst. Charact., 12, 217-224 (1995).
2. C. Andrés, P. Réginault, M. H. Rochat, B. Chaillot, and Y. Pourcelot, Particle size distribution of a powder: comparison of three analytical techniques, Int. J. Pharm., 144, 141-146 (1996).
3. M. Eriksson, G. Alderborn, C. Nyström, F. Podczeck, and J. M. Newton, Comparison between and evaluation of some methods for the assessment of spherity of pellets, Int. J. Pharm., 148, 149-154 (1997).
4. H. S. Hundal, S. Rohani, H. C. Wood, and M. N. Pons, Particle shape characterization using image analysis and neural networks, Powder Technol., 91, 217-227 (1997).
5. F. Podczeck, A shape factor to assess the shape of particles using image analysis, Powder Technol., 93, 47-53 (1997).
6. V. N. Gudivada and V. V. Raghavan, Content-based image retrieval systems, IEEE Comput., 28(9), 18-21 (1995).
7. P. Aigrain, H. Zhang, and D. Petkovic, Content-based representation and retrieval of visual media: a state-of-the-art review, Multimedia Tools Applications, 3, 179-202 (1996).
8. J. R. Bach, C. Fuller, A. Gupta, A. Hampapur, B. Horowitz, R. Humphrey, R. Jain, and C. Shu, The Virage image search engine: an open framework for image management, storage and retrieval for image and video databases, Proc. SPIE-Int. Soc. Opt. Eng., 2670, 76-87 (1996).
9. V. Ng, D. Cheung, and A. Fu, Medical image retrieval by color content, Proc. IEEE Int. Conf. System, Man Cybernetics: Intelligent Syst. 21st Century, 3, 1980-1985 (1995).
10. J. R. Smith and S.-F. Chang, Tools and techniques for color image retrieval, storage and retrieval for image and video databases, Proc. SPIE-Int. Soc. Opt. Eng., 2670, 426-437 (1996).
11. R. Mehrotra and J. E. Gary, Similar-shape retrieval in shape data management, IEEE Comput., 28(9), 57-62 (1995).
12. J. You, H. Shen, and H. A. Cohen, An efficient parallel texture classification for image retrieval, J. Lang. Comput., 8, 359-372 (1997).
13. A. Pentland, R. W. Picard, and S. Scarloff, Photobook: Tools for content-based manipulation of image databases, storage and retrieval for image and video databases II, Proc. SPIE-Int. Soc. Opt. Eng., 2185, 34-47 (1994).
14. T. Caelli and D. Reye, On the classification of image regions by colour, texture and shape, Pattern Recognit., 26, 461-470 (1993).
15. W. Niblack, R. Barber, W. Equitz, M. B. Flickner, E. Glasman, D. Petkovic, P. Yanker, C. Faloutsos, and G. Taubin, The QBIC Project: Querying images by content using color, texture and shape, storage and retrieval for image and video datbases, Proc. SPIE-Int. Soc. Opt. Eng., 1908, 173-181 (1993).
16. C. Faloutsos, R. Barber, M. Flickner, J. Hafner, W. Niblack, and D. Petkovic, Efficient and effective querying by image content, J Intell. Information Syst., 3, 231-262 (1994).
17. J. Ashley, R. Barber, M. Flickner, D. Hafner, D. Lee, W. Niblack, and D. Petkovic, Automatic and semi-automatic methods for image annotation and retrieval in QBIC, storage and retrieval for image and video databases III, Proc. SPIE-Int. Soc. Opt. Eng., 2420, 24-35 (1995).
18. A. Del Bimbo, Image and video databases: Visual browsing, querying and retrieval, J Visual Lang. Comput., 7, 353-359 (1996).
19. M. Sonka, V. Hlavac, and R. Boyle, Image Processing, Analysis and Machine Vision, Chapman & Hall, New York, 1993.
20. J. R. Smith and S.-F. Chang, Visual SEEk: A fully automated content-based image query system. Proc. ACM-Int. Conf. Multimedia, 96, 87-96 (1996).
21. T.-Y. Hou, P. Liu, A. Hsu, and M.-Y. Chiu, Medical image retrieval by spatial features, Proc. IEEE-Int. Conf. Syst., Man Cybernetics, 1364-1369 (1992).
22. A. Gupta, S. Moezzi, A. Taylor, S. Chatterjee, R. Jain, M Goldbaum, and S. Burgess, Content-based retrieval of ophthalmological images, IEEE - Int. Conf. Image Process., 3, 703-706 (1996).
23. B. S. Manjunath and W. Y. Ma, Browsing large satellite and aerial photographs, IEEE - Int. Conf. Image Process., 2, 765-767 (1996).
24. N. Ratha, K. Karu, S. Chen, and A. Jain, A real-time matching system for large fingerprint databases, IEEE Trans. PAMI, 18, 8, 799-812 (1996).
25. A. Soffer and H. Samet, Retrieval by content in symbolic-image databases storage and retrieval for image and video databases IV, Proc. SPIE-Int. Soc. Opt. Eng., 2670, 144-155 (1996).
26. M. Flickner, H. Sawhney, W. Niblack, J. Ashley, Q. Huang, B. Dom, M. Gorkani, J. Hafner, D. Lee, D. Petkovic, D. Steele, and P. Yanker, Query by image and video content: The QBIC System, IEEE Comput., 28(9), 23-31 (1995).