首页> 外文期刊>Journal of Food Measurement and Characterization >Image processing technique to estimate geometric parameters and volume of selected dry beans.
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Image processing technique to estimate geometric parameters and volume of selected dry beans.

机译:图像处理技术可估算所选干豆的几何参数和体积。

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The geometric parameters along with related physical properties of agricultural material are vital to characterize and describe its quality. The application of image processing technique for this purpose can certainly reduce the human drudgery while ensuring quality of produce. The experiments were conducted to classify the shape and then workout the volume of the selected beans using the image processing technique. Green pea, garbanzo, kidney bean, navy bean and pinto bean were procured from the local grocery store for this study. A digital camera was used to capture the images of the ten different beans of each type. The beans were placed in two different orientations (longitudinal and lateral) and image processing technique was used to quantify and process the digital images. The results of image analysis were compared with the data obtained with actual measurements using digital vernier caliper. The related observations like thousand grain weight, bulk density, true density, porosity and weight of selected single grain were also recorded. A linear relationship was seen between the axial dimensions of beans and the pixel value with R2 in the range of 0.64-0.96. The bulk density and true density of the beans were observed to be in the range of 0.71-0.80 and 1.21-1.29 g/cc respectively. The sphericity of the beans varied in the range of 0.55-0.89. Analyses of the acquired images indicate convex geometry for the beans with ellipsoid shape while the same observation was recorded by physical measurements also. A linear relationship was observed between the volumes estimated by image analysis and true volumes of the beans with R2 in the range of 0.80-0.96. The circularity and compactness of the beans lied in the range of 0.69-0.90 and 0.56-0.71
机译:几何参数以及相关农业材料的物理特性对于表征和描述其质量至关重要。为此目的应用图像处理技术肯定可以减少人为繁琐的工作,同时确保产品的质量。进行实验以对形状进行分类,然后使用图像处理技术锻炼所选豆的体积。本研究从当地杂货店采购了绿豌豆,鹰嘴豆,鹰嘴豆,海军豆和斑豆。使用数码相机捕获每种类型的十个不同豆的图像。将咖啡豆放置在两个不同的方向(纵向和横向)上,并使用图像处理技术来量化和处理数字图像。将图像分析的结果与使用数字游标卡尺实际测量获得的数据进行比较。还记录了相关观察值,如千粒重,堆积密度,真实密度,孔隙率和所选单粒重。豆的轴向尺寸与像素值在R 2 在0.64-0.96范围内之间存在线性关系。观察到豆的堆积密度和真实密度分别在0.71-0.80和1.21-1.29 g / cc的范围内。咖啡豆的球形度在0.55-0.89的范围内变化。所获取图像的分析表明具有椭圆形形状的咖啡豆具有凸出的几何形状,同时通过物理测量也记录了相同的观察结果。图像分析估计的体积与R 2 在0.80-0.96范围内的豆的真实体积之间存在线性关系。咖啡豆的圆度和紧密度在0.69-0.90和0.56-0.71的范围内

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