Forensic detection based on color label and oriented texture feature

Tingge Zhu; Jiangbin Zheng; Mingchen Feng; Ying Liu; Wei Liu; Nailiang Kuang; Chao Zhao

doi:10.1007/978-3-030-39431-8_37

Forensic detection based on color label and oriented texture feature

Tingge Zhu, Jiangbin Zheng, Mingchen Feng, Ying Liu, Wei Liu, Nailiang Kuang, Chao Zhao

School of Software

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Copy-move forgery is one of the most tampered means. In this paper, we propose a blind method based on the color label and oriented color texture feature for copy-move detection. Firstly, we compute local color entropy of every pixel, which is grouped into several categories as color labels. Then an image is divided into overlapping blocks, oriented color texture feature of which is extracted. Similar blocks are searched in these blocks with the same color label, and then we fuse these similar block pairs into several regions. According to the linkage relation of these regions, the tampered regions are located. Experiment results have demonstrated that the proposed algorithm has good performance in terms of improved detection accuracy and reduced execution time, at the same time, it also can detect these tampered images inpainted by exemplar-based inpainting technique.

Original language	English
Title of host publication	Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings
Editors	Jinchang Ren, Amir Hussain, Huimin Zhao, Jun Cai, Rongjun Chen, Yinyin Xiao, Kaizhu Huang, Jiangbin Zheng
Publisher	Springer
Pages	383-395
Number of pages	13
ISBN (Print)	9783030394301
DOIs	https://doi.org/10.1007/978-3-030-39431-8_37
State	Published - 2020
Event	10th International Conference on Brain Inspired Cognitive Systems, BICS 2019 - Guangzhou, China Duration: 13 Jul 2019 → 14 Jul 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11691 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Conference on Brain Inspired Cognitive Systems, BICS 2019
Country/Territory	China
City	Guangzhou
Period	13/07/19 → 14/07/19

Keywords

Color label
Digital image forensic
Forged region detection
Oriented texture feature

Access to Document

10.1007/978-3-030-39431-8_37

Cite this

Zhu, T., Zheng, J., Feng, M., Liu, Y., Liu, W., Kuang, N., & Zhao, C. (2020). Forensic detection based on color label and oriented texture feature. In J. Ren, A. Hussain, H. Zhao, J. Cai, R. Chen, Y. Xiao, K. Huang, & J. Zheng (Eds.), Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings (pp. 383-395). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11691 LNAI). Springer. https://doi.org/10.1007/978-3-030-39431-8_37

Zhu, Tingge ; Zheng, Jiangbin ; Feng, Mingchen et al. / Forensic detection based on color label and oriented texture feature. Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings. editor / Jinchang Ren ; Amir Hussain ; Huimin Zhao ; Jun Cai ; Rongjun Chen ; Yinyin Xiao ; Kaizhu Huang ; Jiangbin Zheng. Springer, 2020. pp. 383-395 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{90e21760cc4c4b30ac99a0addbeffbc9,

title = "Forensic detection based on color label and oriented texture feature",

abstract = "Copy-move forgery is one of the most tampered means. In this paper, we propose a blind method based on the color label and oriented color texture feature for copy-move detection. Firstly, we compute local color entropy of every pixel, which is grouped into several categories as color labels. Then an image is divided into overlapping blocks, oriented color texture feature of which is extracted. Similar blocks are searched in these blocks with the same color label, and then we fuse these similar block pairs into several regions. According to the linkage relation of these regions, the tampered regions are located. Experiment results have demonstrated that the proposed algorithm has good performance in terms of improved detection accuracy and reduced execution time, at the same time, it also can detect these tampered images inpainted by exemplar-based inpainting technique.",

keywords = "Color label, Digital image forensic, Forged region detection, Oriented texture feature",

author = "Tingge Zhu and Jiangbin Zheng and Mingchen Feng and Ying Liu and Wei Liu and Nailiang Kuang and Chao Zhao",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; 10th International Conference on Brain Inspired Cognitive Systems, BICS 2019 ; Conference date: 13-07-2019 Through 14-07-2019",

year = "2020",

doi = "10.1007/978-3-030-39431-8_37",

language = "英语",

isbn = "9783030394301",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "383--395",

editor = "Jinchang Ren and Amir Hussain and Huimin Zhao and Jun Cai and Rongjun Chen and Yinyin Xiao and Kaizhu Huang and Jiangbin Zheng",

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}

Zhu, T, Zheng, J, Feng, M, Liu, Y, Liu, W, Kuang, N & Zhao, C 2020, Forensic detection based on color label and oriented texture feature. in J Ren, A Hussain, H Zhao, J Cai, R Chen, Y Xiao, K Huang & J Zheng (eds), Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11691 LNAI, Springer, pp. 383-395, 10th International Conference on Brain Inspired Cognitive Systems, BICS 2019, Guangzhou, China, 13/07/19. https://doi.org/10.1007/978-3-030-39431-8_37

Forensic detection based on color label and oriented texture feature. / Zhu, Tingge; Zheng, Jiangbin; Feng, Mingchen et al.
Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings. ed. / Jinchang Ren; Amir Hussain; Huimin Zhao; Jun Cai; Rongjun Chen; Yinyin Xiao; Kaizhu Huang; Jiangbin Zheng. Springer, 2020. p. 383-395 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11691 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Forensic detection based on color label and oriented texture feature

AU - Zhu, Tingge

AU - Zheng, Jiangbin

AU - Feng, Mingchen

AU - Liu, Ying

AU - Liu, Wei

AU - Kuang, Nailiang

AU - Zhao, Chao

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2020.

PY - 2020

Y1 - 2020

N2 - Copy-move forgery is one of the most tampered means. In this paper, we propose a blind method based on the color label and oriented color texture feature for copy-move detection. Firstly, we compute local color entropy of every pixel, which is grouped into several categories as color labels. Then an image is divided into overlapping blocks, oriented color texture feature of which is extracted. Similar blocks are searched in these blocks with the same color label, and then we fuse these similar block pairs into several regions. According to the linkage relation of these regions, the tampered regions are located. Experiment results have demonstrated that the proposed algorithm has good performance in terms of improved detection accuracy and reduced execution time, at the same time, it also can detect these tampered images inpainted by exemplar-based inpainting technique.

AB - Copy-move forgery is one of the most tampered means. In this paper, we propose a blind method based on the color label and oriented color texture feature for copy-move detection. Firstly, we compute local color entropy of every pixel, which is grouped into several categories as color labels. Then an image is divided into overlapping blocks, oriented color texture feature of which is extracted. Similar blocks are searched in these blocks with the same color label, and then we fuse these similar block pairs into several regions. According to the linkage relation of these regions, the tampered regions are located. Experiment results have demonstrated that the proposed algorithm has good performance in terms of improved detection accuracy and reduced execution time, at the same time, it also can detect these tampered images inpainted by exemplar-based inpainting technique.

KW - Color label

KW - Digital image forensic

KW - Forged region detection

KW - Oriented texture feature

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U2 - 10.1007/978-3-030-39431-8_37

DO - 10.1007/978-3-030-39431-8_37

M3 - 会议稿件

AN - SCOPUS:85080911072

SN - 9783030394301

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 383

EP - 395

BT - Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings

A2 - Ren, Jinchang

A2 - Hussain, Amir

A2 - Zhao, Huimin

A2 - Cai, Jun

A2 - Chen, Rongjun

A2 - Xiao, Yinyin

A2 - Huang, Kaizhu

A2 - Zheng, Jiangbin

PB - Springer

T2 - 10th International Conference on Brain Inspired Cognitive Systems, BICS 2019

Y2 - 13 July 2019 through 14 July 2019

ER -

Zhu T, Zheng J, Feng M, Liu Y, Liu W, Kuang N et al. Forensic detection based on color label and oriented texture feature. In Ren J, Hussain A, Zhao H, Cai J, Chen R, Xiao Y, Huang K, Zheng J, editors, Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings. Springer. 2020. p. 383-395. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-39431-8_37

Forensic detection based on color label and oriented texture feature

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Keywords

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