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Alternative TitleRecognition of Aluminum Casting Based on Texture Feature and SVM Classifier
吴阳1; 刘振华2; 周晓锋2; 张宜弛2
Source Publication计算机系统应用
Contribution Rank2
Keyword铝铸件 灰度共生矩阵 Gabor小波变换 分类 识别
Other AbstractWith the growth of the global economy and the widespread use of aluminum profiles, the global consumption of aluminum castings has been increasing year by year. Due to the different applications, there are a variety of aluminum castings, they have different shapes, structures, colors, textures and so on. As an important aspect of the image processing application, this study analyzes the features of aluminum castings, extracts the texture features of the image by using the gray level co-occurrence matrix and Gabor wavelet transform, respectively, and compares them with the SVM classification algorithm of SVM feature classification, test recognition accuracy, experimental results were compared for the classification of aluminum castings obtained Gabor wavelet transform using both the recognition accuracy or recognition of time on the results are the best.
Document Type期刊论文
Corresponding Author吴阳
Recommended Citation
GB/T 7714
吴阳,刘振华,周晓锋,等. 基于纹理特征和SVM分类器的铝铸件类型识别[J]. 计算机系统应用,2018,27(8):281-285.
APA 吴阳,刘振华,周晓锋,&张宜弛.(2018).基于纹理特征和SVM分类器的铝铸件类型识别.计算机系统应用,27(8),281-285.
MLA 吴阳,et al."基于纹理特征和SVM分类器的铝铸件类型识别".计算机系统应用 27.8(2018):281-285.
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