کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
2450948 | 1109666 | 2010 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Identification of important image features for pork and turkey ham classification using colour and wavelet texture features and genetic selection
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
دانش تغذیه
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
A method to discriminate between various grades of pork and turkey ham was developed using colour and wavelet texture features. Image analysis methods originally developed for predicting the palatability of beef were applied to rapidly identify the ham grade. With high quality digital images of 50–94 slices per ham it was possible to identify the greyscale that best expressed the differences between the various ham grades. The best 10 discriminating image features were then found with a genetic algorithm. Using the best 10 image features, simple linear discriminant analysis models produced 100% correct classifications for both pork and turkey on both calibration and validation sets.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Meat Science - Volume 84, Issue 4, April 2010, Pages 711–717
Journal: Meat Science - Volume 84, Issue 4, April 2010, Pages 711–717
نویسندگان
Patrick Jackman, Da-Wen Sun, Paul Allen, Nektarios A. Valous, Fernando Mendoza, Paddy Ward,