IMPROVING SURF DESCRIPTORS PERFORMANCE FOR IMAGE MATCHING

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

GHARIBI M.; MIRZAKUCHAKI SATTAR

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: ELECTRONIC INDUSTRIES Year:2016 | Volume:7 | Issue:1 Page(s): 75-88

Download Full-Text

Persian Verion

View:

2,161

Download:

Cites:

Information Journal Paper

Title

IMPROVING SURF DESCRIPTORS PERFORMANCE FOR IMAGE MATCHING

Author(s)

GHARIBI M. | MIRZAKUCHAKI SATTAR | Issue Writer Certificate

Keywords

MATCHINGQ2

INTEREST POINTSQ2

DESCRIPTORSQ2

LOCAL FEATUREQ2

Abstract

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.

Cites

No record.

References

No record.

Cite

APA: Copy

GHARIBI, M., & MIRZAKUCHAKI, SATTAR. (2016). IMPROVING SURF DESCRIPTORS PERFORMANCE FOR IMAGE MATCHING. ELECTRONIC INDUSTRIES, 7(1), 75-88. SID. https://sid.ir/paper/229554/en

Vancouver: Copy

GHARIBI M., MIRZAKUCHAKI SATTAR. IMPROVING SURF DESCRIPTORS PERFORMANCE FOR IMAGE MATCHING. ELECTRONIC INDUSTRIES[Internet]. 2016;7(1):75-88. Available from: https://sid.ir/paper/229554/en

IEEE: Copy

M. GHARIBI, and SATTAR MIRZAKUCHAKI, “IMPROVING SURF DESCRIPTORS PERFORMANCE FOR IMAGE MATCHING,” ELECTRONIC INDUSTRIES, vol. 7, no. 1, pp. 75–88, 2016, [Online]. Available: https://sid.ir/paper/229554/en

Related Journal Papers