Farsi Handwritten Digits Recognition based on Interval Type-II Fuzzy Fusion of Support Vector Machines

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.

Mahmoodzadeh Azar; Agahi Hamed

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

Journal Paper

Paper Information

Journal: JOURNAL OF ADVANCED SIGNAL PROCESSING Year:2021 | Volume:4 | Issue:2 (6) Page(s): 251-262

Download Full-Text

Persian Verion

View:

130

Download:

Cites:

Information Journal Paper

Title

Farsi Handwritten Digits Recognition based on Interval Type-II Fuzzy Fusion of Support Vector Machines

Author(s)

Mahmoodzadeh Azar | Agahi Hamed | Issue Writer Certificate

Keywords

Classification

classifiers ensemble

Farsi handwritten digits

feature selection

interval type-II fuzzy inference system

Abstract

The problem of automatic handwritten context recognition has received considerable attention of many researchers. In this paper, a fusion system is proposed to enhance the recognition accuracy of Farsi handwritten digits. The proposed approach consists of a preparation process and two main phases. In the preparation process, some pre-processing operations are performed on the image. Then some features are extracted, among which a multi-objective particle swarm optimization selects more effective ones. For every image, these optimal features are given as the input data to the classifiers. In the first main phase, training datasets are used to construct three different SVMs. In order to achieve better results, the adaptive best-mass gravitational search algorithm is utilized to adjust the SVMs parameters. In the second main phase, an interval type– II fuzzy inference system receives the SVMs outputs and by combining them, it presents a more accurate estimation of the digit in the image. The results of applying the proposed approach to the problem of scanned Farsi handwritten digits in the standard HODA database demonstrated that this algorithm attains high accuracy, precision and recall performance indices, comparing to other existing methods.

Cites

No record.

References

No record.

Cite

APA: Copy

Mahmoodzadeh, Azar, & Agahi, Hamed. (2021). Farsi Handwritten Digits Recognition based on Interval Type-II Fuzzy Fusion of Support Vector Machines. JOURNAL OF ADVANCED SIGNAL PROCESSING, 4(2 (6) ), 251-262. SID. https://sid.ir/paper/961967/en

Vancouver: Copy

Mahmoodzadeh Azar, Agahi Hamed. Farsi Handwritten Digits Recognition based on Interval Type-II Fuzzy Fusion of Support Vector Machines. JOURNAL OF ADVANCED SIGNAL PROCESSING[Internet]. 2021;4(2 (6) ):251-262. Available from: https://sid.ir/paper/961967/en

IEEE: Copy

Azar Mahmoodzadeh, and Hamed Agahi, “Farsi Handwritten Digits Recognition based on Interval Type-II Fuzzy Fusion of Support Vector Machines,” JOURNAL OF ADVANCED SIGNAL PROCESSING, vol. 4, no. 2 (6) , pp. 251–262, 2021, [Online]. Available: https://sid.ir/paper/961967/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops