کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
532128 869910 2014 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Discriminant analysis and similarity measure
ترجمه فارسی عنوان
آنالیز تشخیصی و تشابه آن
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی


• The connection between the cosine similarity and the Bayes decision rule.
• Discuss some inherent challenges of the cosine similarity.
• A new similarity measure that integrates both angular and distance measure.
• Experiments on the FRGC version 2 database (36,818 images).

The cosine similarity measure is often applied after discriminant analysis in pattern recognition. This paper first analyzes why the cosine similarity is preferred by establishing the connection between the cosine similarity based decision rule in the discriminant analysis framework and the Bayes decision rule for minimum error. The paper then investigates the challenges inherent of the cosine similarity and presents a new similarity that overcomes these challenges. The contributions of the paper are thus three-fold. First, the application of the cosine similarity after discriminant analysis is discovered to have its theoretical roots in the Bayes decision rule. Second, some inherent problems of the cosine similarity such as its inadequacy in addressing distance and angular measures are discussed. Finally, a new similarity measure, which overcomes the problems by integrating the absolute value of the angular measure and the lp norm (the distance measure), is presented to enhance pattern recognition performance. The effectiveness of the proposed new similarity measure in the discriminant analysis framework is evaluated using a large scale, grand challenge problem, namely, the Face Recognition Grand Challenge (FRGC) problem. Experimental results using 36,818 FRGC images on the most challenging FRGC experiment, the FRGC Experiment 4, show that the new similarity measure improves face recognition performance upon other popular similarity measures, such as the cosine similarity measure, the normalized correlation, and the Euclidean distance measure.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 47, Issue 1, January 2014, Pages 359–367
نویسندگان
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