کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6940655 | 1450016 | 2018 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Enhancing image registration performance by incorporating distribution and spatial distance of local descriptors
ترجمه فارسی عنوان
بهبود عملکرد ثبت نام تصویر با استفاده از توزیع و فاصله فضایی توصیفگرهای محلی
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
A data dependency similarity measure called mp-dissimilarity has been recently proposed. Unlike âp-norm distance which is widely used in calculating the similarity between vectors, mp-dissimilarity takes into account the relative positions of the two vectors with respect to the rest of the data. This paper investigates the potential of mp-dissimilarity in matching local image descriptors. Moreover, three new matching strategies are proposed by considering both âp-norm distance and mp-dissimilarity. Our proposed matching strategies are extensively evaluated against âp-norm distance and mp-dissimilarity on a few benchmark datasets. Experimental results show that mp-dissimilarity is a promising alternative to âp-norm distance in matching local descriptors. The proposed matching strategies outperform both âp-norm distance and mp-dissimilarity in matching accuracy. One of our proposed matching strategies is comparable to âp-norm distance in terms of recall vs 1-precision.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 103, 1 February 2018, Pages 46-52
Journal: Pattern Recognition Letters - Volume 103, 1 February 2018, Pages 46-52
نویسندگان
Guohua Lv, Shyh Wei Teng, Guojun Lu,