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 source preferred by Jian Jun Zhang, Jian Chang and Ehtzaz Chaudhry

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 04:48 on February 24, 2018.