Miao Teng, Zhao Chunjiang, Guo Xinyu, Lu Shenglian, Wen Weiliang. Visual simulating appearance of plant leaves infected by disease and insect pests[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2014, 30(2): 169-175. DOI: 10.3969/j.issn.1002-6819.2014.02.022
    Citation: Miao Teng, Zhao Chunjiang, Guo Xinyu, Lu Shenglian, Wen Weiliang. Visual simulating appearance of plant leaves infected by disease and insect pests[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2014, 30(2): 169-175. DOI: 10.3969/j.issn.1002-6819.2014.02.022

    Visual simulating appearance of plant leaves infected by disease and insect pests

    • Abstract: 3D agricultural scene under the condition of plant disease and insect pests is very difficult to simulate because of the complex appearance characteristics and severe apparent changes of the disease spots. The realistic appearance of plant leaves infected by the disease can't be obtained by the current methods. This paper presents a method to simulate the appearance of plant leaves infected by the disease. We assume that the disease spots uniformly distribute on the blade surface, spread from the spots center to the surrounding, and the shapes of the same kind of spots are similar. Based on these assumptions, the celluar bias function is used for controlling the shape, distribution and diffusion movement of the disease spot, and also for generating a 2D celluar texture image whose pixels represent the disease degree of any point on the blade surface. A degree parameter (in the range of 0 to 1) is used to adjust the pixel value of celluar texture to control the disease status, and the degree parameter equals 0 means there is no disease, and vice versa. We observed that some diseases can produce mildew layers on the leaf blade surface and which has volumetric, granular and arch form surface nature. In order to simulate the volumetric nature, the shell model is integrated into the approach. We use 15 passes to construct the shell model and use the degree parameter to discard the pixels which are not the mildew layers. For realistically rendering the grainy nature, the Perlin noise is applied to disturb the degree parameter for removing some pixels which belong to the mildew layers. With the purpose of generating an arch form mildew layer surface, we use the degree parameter to discard the pixels which belong to the larger passes of the shell model. Through this operation, the shell will present the height characteristics due to the gradual accumulation of the disease hyphae, middle part of the mildew layer is higher and the marginal part is lower. The optical property of the mildew layer is very hard to modeling because of the heterogeneous internal structure and the subsurface scattering property. In the approach, we construct a parameterized BRDF model to approximate the actual appearance. Owing to covering of the mildew, plant leaves ageing phenomenon happens. For rendering it, a leaf optical model with physiological factors is adopted, which can simulate the aging process by controlling some physiological parameters such as chlorophyll content and carotene content. The new method can be easily integrated with disease early warning model to simulate the disease appearance with different disease index or different environment parameters such as temperature and humidity. We realized the algorithm in this paper using OpenGL, and by comparing the rendering results to some actual disease images, we found that the method can realistically rendering the appearance of the plant leaves infected by the disease and insect pest. The research can provide a powerful tool to produce animations for agricultural science training. In the future work, we will focus on observing and analyzing some actual disease spread process to construct a more accurate parameter model for calculating the shape and the distribution of the disease spots.
    • loading

    Catalog

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return