نویسندگان
1 دانشگاه علم و صنعت ایران
2 دانشگاه علم و صنعت
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Image matching is one of the important issues in the machine vision science and is the basis of many
systems in the field of artificial intelligence. It is mainly used in object recognition in robotic
applications, data acquisition and analyzing the received data from satellite, object tracking in the
military applications and image retrieval. The aim of this paper is to introduce an improved scale and
rotation invariant algorithm based on the local feature for image matching demonstrating good
performance in the case of intensity and blur changes. One of the important algorithms for image
matching is SURF. Recent algorithms that are proposed in this field are divided into two groups. The
first group have better performance than SURF but their running time have been increased. The second
group reach a lower running time compared with SURF but they scarify the performance. This paper
proposes a novel algorithm that has better performance than SURF with no running time overhead.
کلیدواژهها [English]
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