Realistic texture synthesis for point-based fruitage phenotype

This data was imported from PubMed:

Authors: Yang, H., Chang, J., He, D., Geng, N., Wang, M., Zhang, J., Jing, X. and Chaudhry, E.

http://eprints.bournemouth.ac.uk/30125/

Journal: Comput Biol Med

Volume: 92

Pages: 42-54

eISSN: 1879-0534

DOI: 10.1016/j.compbiomed.2016.08.017

Although current 3D scanner technology can acquire textural images from a point model, visible seams in the image, inconvenient data acquisition and occupancy of a large space during use are points of concern for outdoor fruit models. In this paper, an SPSDW (simplification and perception based subdivision followed by down-sampling weighted average) method is proposed to balance memory usage and texture synthesis quality using a crop fruit, such as apples, as a research subject for a point-based fruit model. First, the quadtree method is improved to make splitting more efficient, and a reasonable texton descriptor is defined to promote query efficiency. Then, the color perception feature is extracted from the image for all pixels. Next, an advanced sub-division scheme and down-sampling strategy are designed to optimize memory space. Finally, a weighted oversampling method is proposed for high-quality texture mixing. This experiment demonstrates that the SPSDW method preserves the mixed texture more realistically and smoothly and preserves color memory up to 94%, 84.7% and 85.7% better than the two-dimesional processing, truncating scalar quantitative and color vision model methods, respectively.

This data was imported from Scopus:

Authors: Yang, H.J., Chang, J., He, D., Geng, N., Wang, M., Zhang, J.J., Jing, X. and Chaudhry, E.

http://eprints.bournemouth.ac.uk/30125/

Journal: Computers in Biology and Medicine

Volume: 92

Pages: 42-54

eISSN: 1879-0534

ISSN: 0010-4825

DOI: 10.1016/j.compbiomed.2016.08.017

© 2017 Elsevier Ltd Although current 3D scanner technology can acquire textural images from a point model, visible seams in the image, inconvenient data acquisition and occupancy of a large space during use are points of concern for outdoor fruit models. In this paper, an SPSDW (simplification and perception based subdivision followed by down-sampling weighted average) method is proposed to balance memory usage and texture synthesis quality using a crop fruit, such as apples, as a research subject for a point-based fruit model. First, the quadtree method is improved to make splitting more efficient, and a reasonable texton descriptor is defined to promote query efficiency. Then, the color perception feature is extracted from the image for all pixels. Next, an advanced sub-division scheme and down-sampling strategy are designed to optimize memory space. Finally, a weighted oversampling method is proposed for high-quality texture mixing. This experiment demonstrates that the SPSDW method preserves the mixed texture more realistically and smoothly and preserves color memory up to 94%, 84.7% and 85.7% better than the two-dimesional processing, truncating scalar quantitative and color vision model methods, respectively.

This data was imported from Web of Science (Lite):

Authors: Yang, H., Chang, J., He, D., Geng, N., Wang, M., Zhang, J., Jing, X. and Chaudhry, E.

http://eprints.bournemouth.ac.uk/30125/

Journal: COMPUTERS IN BIOLOGY AND MEDICINE

Volume: 92

Pages: 42-54

eISSN: 1879-0534

ISSN: 0010-4825

DOI: 10.1016/j.compbiomed.2016.08.017

The data on this page was last updated at 04:51 on October 15, 2018.