Raisin quality classification using least squares support vector machine (LSSVM) based on combined color and texture features.

Xinjie Yu; Kangsheng Liu; Di Wu; Yong He

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Raisin quality classification using least squares support vector machine (LSSVM) based on combined color and texture features.

机译：基于组合的颜色和纹理特征，使用最小二乘支持向量机（LSSVM）对葡萄干进行质量分类。

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In this paper, an approach based on combined color and texture features to classify raisins is presented. Least squares support vector machine (LSSVM), linear discriminant analysis, and soft independent modeling of class analogy were used to construct classification models. A total of 480 images were captured from four grades of raisin samples by a Basler 601 fc IEEE1394 digital camera, 200 images were randomly selected to create calibration model (training set), and remaining images were used to verify the model (prediction set). Color features and texture features were obtained from two color spaces: red-green-blue and hue-saturation-intensity using histogram method and gray level co-occurrence matrix method, respectively. Our results indicate that the best performance with about 95% of average correct answer rate is achieved by LSSVM using combined color and texture features from HSI color space. This result is significantly higher than the performance of solely used color or texture features. The combined color and texture features coupled with a LSSVM classifier are a highly accurate way for raisin quality classification

机译：本文提出了一种基于颜色和纹理特征组合的葡萄干分类方法。最小二乘支持向量机（LSSVM），线性判别分析和类比的软独立建模用于构建分类模型。通过Basler 601 fc IEEE1394数码相机从四个等级的葡萄干样品中捕获了480张图像，随机选择了200张图像以创建校准模型（训练集），其余图像用于验证模型（预测集）。使用直方图法和灰度共生矩阵法分别从红，绿，蓝和色相饱和度这两个颜色空间获得颜色特征和纹理特征。我们的结果表明，LSSVM使用HSI颜色空间中的组合颜色和纹理特征，可获得约95％的平均正确答案率的最佳性能。该结果明显高于单独使用的颜色或纹理特征的性能。结合了颜色和纹理特征以及LSSVM分类器，是葡萄干质量分类的高精度方法

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《Food and bioprocess technology》 |2012年第5期|共12页
作者
Xinjie Yu; Kangsheng Liu; Di Wu; Yong He;
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正文语种 eng
中图分类食品工业;
关键词
Raisin; Classification; Color features; Texture features; Least squares support vector machine;

机译：葡萄干;分类;颜色特征;纹理特征;最小二乘支持向量机;

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1. Raisin quality classification using least squares support vector machine (LSSVM) based on combined color and texture features. [J] . Xinjie Yu, Kangsheng Liu, Di Wu, Food and bioprocess technology . 2012,第5期

机译：基于组合的颜色和纹理特征，使用最小二乘支持向量机（LSSVM）对葡萄干进行质量分类。
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Raisin quality classification using least squares support vector machine (LSSVM) based on combined color and texture features.

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