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Heterogeneous scene matching based on the gradient direction distribution field.

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Title: Heterogeneous scene matching based on the gradient direction distribution field.
Authors: Li, Qingge1 (AUTHOR), Lu, Ruitao1,2 (AUTHOR) lrt19880220@163.com, Yang, Xiaogang1 (AUTHOR), Wang, Siyu1 (AUTHOR), Shen, Tong1 (AUTHOR), Xia, Wenxin1 (AUTHOR), Wei, Zhaoying3 (AUTHOR)
Source: EURASIP Journal on Image & Video Processing. 4/27/2023, Vol. 2023 Issue 1, p1-17. 17p.
Subjects: Computer vision, Visual fields, Computer engineering
Abstract: Heterogeneous scene matching is a key technology in the field of computer vision. The image rotation problem is popular and difficult in the field of heterogeneous scene matching. In this paper, a heterogeneous scene matching method based on the gradient direction distribution field is proposed, and distributed field theory is introduced into heterogeneous scene matching for the first time. First, the distribution field of the gradient direction is constructed and fuzzified, and then the effective regions are selected. Then, the distribution field of the main direction is defined to solve the matching errors due to the existence of rotational transformations between heterogeneous source images. Third, the chi-square distance is introduced as a similarity measure. Finally, the hill-climbing method search strategy, which greatly improves the efficiency of the algorithm, is adopted. Experimental results on 8 pairs of infrared and visible heterogeneous images demonstrate that the proposed method outperforms the other state-of-the-art region-based matching methods in terms of the robustness, accuracy, and real-time performance. [ABSTRACT FROM AUTHOR]
Copyright of EURASIP Journal on Image & Video Processing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Heterogeneous scene matching based on the gradient direction distribution field.
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  Data: <searchLink fieldCode="AR" term="%22Li%2C+Qingge%22">Li, Qingge</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lu%2C+Ruitao%22">Lu, Ruitao</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> lrt19880220@163.com</i><br /><searchLink fieldCode="AR" term="%22Yang%2C+Xiaogang%22">Yang, Xiaogang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Siyu%22">Wang, Siyu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shen%2C+Tong%22">Shen, Tong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xia%2C+Wenxin%22">Xia, Wenxin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wei%2C+Zhaoying%22">Wei, Zhaoying</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22EURASIP+Journal+on+Image+%26+Video+Processing%22">EURASIP Journal on Image & Video Processing</searchLink>. 4/27/2023, Vol. 2023 Issue 1, p1-17. 17p.
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  Data: <searchLink fieldCode="DE" term="%22Computer+vision%22">Computer vision</searchLink><br /><searchLink fieldCode="DE" term="%22Visual+fields%22">Visual fields</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+engineering%22">Computer engineering</searchLink>
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  Data: Heterogeneous scene matching is a key technology in the field of computer vision. The image rotation problem is popular and difficult in the field of heterogeneous scene matching. In this paper, a heterogeneous scene matching method based on the gradient direction distribution field is proposed, and distributed field theory is introduced into heterogeneous scene matching for the first time. First, the distribution field of the gradient direction is constructed and fuzzified, and then the effective regions are selected. Then, the distribution field of the main direction is defined to solve the matching errors due to the existence of rotational transformations between heterogeneous source images. Third, the chi-square distance is introduced as a similarity measure. Finally, the hill-climbing method search strategy, which greatly improves the efficiency of the algorithm, is adopted. Experimental results on 8 pairs of infrared and visible heterogeneous images demonstrate that the proposed method outperforms the other state-of-the-art region-based matching methods in terms of the robustness, accuracy, and real-time performance. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of EURASIP Journal on Image & Video Processing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: 4/27/2023
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