کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5471865 | 1519505 | 2017 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Bag-of-Feature model for sweet and bitter almond classification
ترجمه فارسی عنوان
مدل کیسه ای از ویژگی های سبک شیرین و تلخ بادام
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کلمات کلیدی
بادام، کیف از ویژگی، طبقه بندی، نقطه کلیدی، بینایی ماشین،
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
چکیده انگلیسی
The use of computer vision techniques in post-harvest processing of agricultural products has increased considerably in recent years due to their non-destructive and rapid monitoring abilities. Image processing, combined with pattern recognition, has been applied in fruit sorting and classification. In this study, a Bag-of-Feature (BoF) model is used for the classification of 20 sweet and bitter almond varieties. Harris, Harris-Laplace, Hessian, Hessian-Laplace and Maximally Stable Extremal Regions (MSER) keypoint detectors along with a Scale Invariant Feature Transform (SIFT) descriptor are used in the BoF model. The k-means clustering method is applied for building a codebook from keypoint descriptors. The performance of 3 classifiers, which were k-Nearest Neighbour (k-NN), linear and chi-square Support Vector Machine (L-SVM and Chi-SVM, respectively) were compared using classification results in the model. It was observed that the Chi-SVM classifier outperformed the k-NN and L-SVM classifiers. Using the BoF model, it was possible to detect and classify sweet and bitter varieties with high overall accuracy.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biosystems Engineering - Volume 156, April 2017, Pages 51-60
Journal: Biosystems Engineering - Volume 156, April 2017, Pages 51-60
نویسندگان
Abozar Nasirahmadi, Seyed-Hassan Miraei Ashtiani,