A Fuzzy Kernel Maximum Margin Criterion for Image Feature Extraction

المؤلف

Xuan, Shibin

المصدر

Mathematical Problems in Engineering

العدد

المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-13، 13ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2015-04-14

دولة النشر

مصر

عدد الصفحات

13

التخصصات الرئيسية

هندسة مدنية

الملخص EN

Based on kernel principal component analysis, fuzzy set theory, and maximum margin criterion, a novel image feature extraction and recognition method, called fuzzy kernel maximum margin criterion (FKMMC), is proposed.

In the proposed method, two new fuzzy scatter matrixes are redefined.

The new fuzzy scatter matrix can reflect fully the relation between fuzzy membership degree and the offset of the training sample to subclass center.

Besides, a concise reliable computational method of the fuzzy between-class scatter matrix is provided.

Experimental results on four face databases (AR, extended Yale B, GTFD, and FERET) demonstrate that the proposed method outperforms other methods.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Xuan, Shibin. 2015. A Fuzzy Kernel Maximum Margin Criterion for Image Feature Extraction. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1074370

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Xuan, Shibin. A Fuzzy Kernel Maximum Margin Criterion for Image Feature Extraction. Mathematical Problems in Engineering No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1074370

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Xuan, Shibin. A Fuzzy Kernel Maximum Margin Criterion for Image Feature Extraction. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1074370

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1074370