کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10344533 | 697850 | 2013 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Assessment of acrosome state in boar spermatozoa heads using n-contours descriptor and RLVQ
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
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چکیده انگلیسی
This paper proposes a method for assessing the acrosome state of boar spermatozoa heads using digital image processing. We use gray level images in which spermatozoa have been labeled as acrosome-intact or acrosome damaged using the information of a coupled fluorescent image. The heads are segmented obtaining the outer head contour. A set of “n” inner contours separated by a logarithmic distance function is calculated later. For each point of the, in this case, seven contours a number of local texture features are computed. We have compared the classification performance of Relevance Learning Vector Quantization, class conditional means and KNN, employing cross-validation for the evaluation. Gradient magnitude data offer the best result with an overall test error of only 1%. This result outperforms previously applied methods and suggests this approach as an interesting automatized approach to this veterinarian problem.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Methods and Programs in Biomedicine - Volume 111, Issue 3, September 2013, Pages 525-536
Journal: Computer Methods and Programs in Biomedicine - Volume 111, Issue 3, September 2013, Pages 525-536
نویسندگان
E. Alegre, M. Biehl, N. Petkov, L. Sanchez,