Skip to main content

Realistic texture synthesis for point-based fruitage phenotype.

Yang, H.J., Chang, J., He, D., Geng, N., Wang, M., Zhang, J. J., Jing, X. and Chaudhry, E., 2018. Realistic texture synthesis for point-based fruitage phenotype. Computers in Biology and Medicine, 92 (January), 42 - 54.

Full text available as:

s1-ln23050879-820303744-1939656818Hwf-320396387IdV-159745333923050879PDF_HI0001.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.


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.

Item Type:Article
Uncontrolled Keywords:Fruitage morphology ; Texton division ; Texture sampling ; Texture synthesis
Group:Faculty of Media & Communication
ID Code:30125
Deposited By: Symplectic RT2
Deposited On:15 Jan 2018 16:21
Last Modified:14 Mar 2022 14:08


Downloads per month over past year

More statistics for this item...
Repository Staff Only -