Multi-Purpose Forensics of Image Manipulations Using Residual-Based Feature Article Swipe

View

Anjie Peng , Kang Deng , Shenghai Luo , Hui Zeng ·

YOU? · · 2020 · Open Access · · DOI: https://doi.org/10.32604/cmc.2020.011006

The multi-purpose forensics is an important tool for forge image detection. In this paper, we propose a universal feature set for the multi-purpose forensics which is capable of simultaneously identifying several typical image manipulations, including spatial low-pass Gaussian blurring, median filtering, re-sampling, and JPEG compression. To eliminate the influences caused by diverse image contents on the effectiveness and robustness of the feature, a residual group which contains several highpass filtered residuals is introduced. The partial correlation coefficient is exploited from the residual group to purely measure neighborhood correlations in a linear way. Besides that, we also combine autoregressive coefficient and transition probability to form the proposed composite feature which is used to measure how manipulations change the neighborhood relationships in both linear and non-linear way. After a series of dimension reductions, the proposed feature set can accelerate the training and testing for the multipurpose forensics. The proposed feature set is then fed into a multi-classifier to train a multi-purpose detector. Experimental results show that the proposed detector can identify several typical image manipulations, and is superior to the complicated deep CNN-based methods in terms of detection accuracy and time efficiency for JPEG compressed image with low resolution.

Related Topics

Artificial Intelligence

Concepts

Artificial intelligence Pattern recognition (psychology) Computer science Residual Feature extraction Robustness (evolution) Feature (linguistics) Blob detection Detector Computer vision Image processing Image (mathematics) Algorithm Edge detection Chemistry Telecommunications Gene Linguistics Philosophy Biochemistry

Metadata

Type: article
Language: en
Landing Page: https://doi.org/10.32604/cmc.2020.011006
OA Status: diamond
Cited By: 4
Related Works: 10
OpenAlex ID: https://openalex.org/W4229517718

All OpenAlex metadata

Raw OpenAlex JSON

OpenAlex ID: https://openalex.org/W4229517718

Canonical identifier for this work in OpenAlex
DOI: https://doi.org/10.32604/cmc.2020.011006

Digital Object Identifier
Title: Multi-Purpose Forensics of Image Manipulations Using Residual-Based Feature

Work title
Type: article

OpenAlex work type
Language: en

Primary language
Publication year: 2020

Year of publication
Publication date: 2020-01-01

Full publication date if available
Authors: Anjie Peng, Kang Deng, Shenghai Luo, Hui Zeng

List of authors in order
Landing page: https://doi.org/10.32604/cmc.2020.011006

Publisher landing page
Open access: Yes

Whether a free full text is available
OA status: diamond

Open access status per OpenAlex
OA URL: https://doi.org/10.32604/cmc.2020.011006

Direct OA link when available
Concepts: Artificial intelligence, Pattern recognition (psychology), Computer science, Residual, Feature extraction, Robustness (evolution), Feature (linguistics), Blob detection, Detector, Computer vision, Image processing, Image (mathematics), Algorithm, Edge detection, Chemistry, Telecommunications, Gene, Linguistics, Philosophy, Biochemistry

Top concepts (fields/topics) attached by OpenAlex
Cited by: 4

Total citation count in OpenAlex
Citations by year (recent): 2022: 1, 2021: 3

Per-year citation counts (last 5 years)
Related works (count): 10

Other works algorithmically related by OpenAlex

Full payload

id	https://openalex.org/W4229517718
doi	https://doi.org/10.32604/cmc.2020.011006
ids.doi	https://doi.org/10.32604/cmc.2020.011006
ids.openalex	https://openalex.org/W4229517718
fwci	0.41986927
type	article
title	Multi-Purpose Forensics of Image Manipulations Using Residual-Based Feature
biblio.issue	3
biblio.volume	65
biblio.last_page	2231
biblio.first_page	2217
topics[0].id	https://openalex.org/T12357
topics[0].field.id	https://openalex.org/fields/17
topics[0].field.display_name	Computer Science
topics[0].score	0.9998000264167786
topics[0].domain.id	https://openalex.org/domains/3
topics[0].domain.display_name	Physical Sciences
topics[0].subfield.id	https://openalex.org/subfields/1707
topics[0].subfield.display_name	Computer Vision and Pattern Recognition
topics[0].display_name	Digital Media Forensic Detection
topics[1].id	https://openalex.org/T13114
topics[1].field.id	https://openalex.org/fields/22
topics[1].field.display_name	Engineering
topics[1].score	0.9894999861717224
topics[1].domain.id	https://openalex.org/domains/3
topics[1].domain.display_name	Physical Sciences
topics[1].subfield.id	https://openalex.org/subfields/2214
topics[1].subfield.display_name	Media Technology
topics[1].display_name	Image Processing Techniques and Applications
topics[2].id	https://openalex.org/T10775
topics[2].field.id	https://openalex.org/fields/17
topics[2].field.display_name	Computer Science
topics[2].score	0.9807000160217285
topics[2].domain.id	https://openalex.org/domains/3
topics[2].domain.display_name	Physical Sciences
topics[2].subfield.id	https://openalex.org/subfields/1707
topics[2].subfield.display_name	Computer Vision and Pattern Recognition
topics[2].display_name	Generative Adversarial Networks and Image Synthesis
is_xpac	False
apc_list
apc_paid
concepts[0].id	https://openalex.org/C154945302
concepts[0].level	1
concepts[0].score	0.7314352989196777
concepts[0].wikidata	https://www.wikidata.org/wiki/Q11660
concepts[0].display_name	Artificial intelligence
concepts[1].id	https://openalex.org/C153180895
concepts[1].level	2
concepts[1].score	0.682441234588623
concepts[1].wikidata	https://www.wikidata.org/wiki/Q7148389
concepts[1].display_name	Pattern recognition (psychology)
concepts[2].id	https://openalex.org/C41008148
concepts[2].level	0
concepts[2].score	0.6702744960784912
concepts[2].wikidata	https://www.wikidata.org/wiki/Q21198
concepts[2].display_name	Computer science
concepts[3].id	https://openalex.org/C155512373
concepts[3].level	2
concepts[3].score	0.6092758178710938
concepts[3].wikidata	https://www.wikidata.org/wiki/Q287450
concepts[3].display_name	Residual
concepts[4].id	https://openalex.org/C52622490
concepts[4].level	2
concepts[4].score	0.5148147940635681
concepts[4].wikidata	https://www.wikidata.org/wiki/Q1026626
concepts[4].display_name	Feature extraction
concepts[5].id	https://openalex.org/C63479239
concepts[5].level	3
concepts[5].score	0.5119863152503967
concepts[5].wikidata	https://www.wikidata.org/wiki/Q7353546
concepts[5].display_name	Robustness (evolution)
concepts[6].id	https://openalex.org/C2776401178
concepts[6].level	2
concepts[6].score	0.49045440554618835
concepts[6].wikidata	https://www.wikidata.org/wiki/Q12050496
concepts[6].display_name	Feature (linguistics)
concepts[7].id	https://openalex.org/C29168087
concepts[7].level	5
concepts[7].score	0.4466908276081085
concepts[7].wikidata	https://www.wikidata.org/wiki/Q1026711
concepts[7].display_name	Blob detection
concepts[8].id	https://openalex.org/C94915269
concepts[8].level	2
concepts[8].score	0.4171158969402313
concepts[8].wikidata	https://www.wikidata.org/wiki/Q1834857
concepts[8].display_name	Detector
concepts[9].id	https://openalex.org/C31972630
concepts[9].level	1
concepts[9].score	0.4124518036842346
concepts[9].wikidata	https://www.wikidata.org/wiki/Q844240
concepts[9].display_name	Computer vision
concepts[10].id	https://openalex.org/C9417928
concepts[10].level	3
concepts[10].score	0.32130277156829834
concepts[10].wikidata	https://www.wikidata.org/wiki/Q1070689
concepts[10].display_name	Image processing
concepts[11].id	https://openalex.org/C115961682
concepts[11].level	2
concepts[11].score	0.253638356924057
concepts[11].wikidata	https://www.wikidata.org/wiki/Q860623
concepts[11].display_name	Image (mathematics)
concepts[12].id	https://openalex.org/C11413529
concepts[12].level	1
concepts[12].score	0.1677323281764984
concepts[12].wikidata	https://www.wikidata.org/wiki/Q8366
concepts[12].display_name	Algorithm
concepts[13].id	https://openalex.org/C193536780
concepts[13].level	4
concepts[13].score	0.09157824516296387
concepts[13].wikidata	https://www.wikidata.org/wiki/Q1513153
concepts[13].display_name	Edge detection
concepts[14].id	https://openalex.org/C185592680
concepts[14].level	0
concepts[14].score	0.0
concepts[14].wikidata	https://www.wikidata.org/wiki/Q2329
concepts[14].display_name	Chemistry
concepts[15].id	https://openalex.org/C76155785
concepts[15].level	1
concepts[15].score	0.0
concepts[15].wikidata	https://www.wikidata.org/wiki/Q418
concepts[15].display_name	Telecommunications
concepts[16].id	https://openalex.org/C104317684
concepts[16].level	2
concepts[16].score	0.0
concepts[16].wikidata	https://www.wikidata.org/wiki/Q7187
concepts[16].display_name	Gene
concepts[17].id	https://openalex.org/C41895202
concepts[17].level	1
concepts[17].score	0.0
concepts[17].wikidata	https://www.wikidata.org/wiki/Q8162
concepts[17].display_name	Linguistics
concepts[18].id	https://openalex.org/C138885662
concepts[18].level	0
concepts[18].score	0.0
concepts[18].wikidata	https://www.wikidata.org/wiki/Q5891
concepts[18].display_name	Philosophy
concepts[19].id	https://openalex.org/C55493867
concepts[19].level	1
concepts[19].score	0.0
concepts[19].wikidata	https://www.wikidata.org/wiki/Q7094
concepts[19].display_name	Biochemistry
keywords[0].id	https://openalex.org/keywords/artificial-intelligence
keywords[0].score	0.7314352989196777
keywords[0].display_name	Artificial intelligence
keywords[1].id	https://openalex.org/keywords/pattern-recognition
keywords[1].score	0.682441234588623
keywords[1].display_name	Pattern recognition (psychology)
keywords[2].id	https://openalex.org/keywords/computer-science
keywords[2].score	0.6702744960784912
keywords[2].display_name	Computer science
keywords[3].id	https://openalex.org/keywords/residual
keywords[3].score	0.6092758178710938
keywords[3].display_name	Residual
keywords[4].id	https://openalex.org/keywords/feature-extraction
keywords[4].score	0.5148147940635681
keywords[4].display_name	Feature extraction
keywords[5].id	https://openalex.org/keywords/robustness
keywords[5].score	0.5119863152503967
keywords[5].display_name	Robustness (evolution)
keywords[6].id	https://openalex.org/keywords/feature
keywords[6].score	0.49045440554618835
keywords[6].display_name	Feature (linguistics)
keywords[7].id	https://openalex.org/keywords/blob-detection
keywords[7].score	0.4466908276081085
keywords[7].display_name	Blob detection
keywords[8].id	https://openalex.org/keywords/detector
keywords[8].score	0.4171158969402313
keywords[8].display_name	Detector
keywords[9].id	https://openalex.org/keywords/computer-vision
keywords[9].score	0.4124518036842346
keywords[9].display_name	Computer vision
keywords[10].id	https://openalex.org/keywords/image-processing
keywords[10].score	0.32130277156829834
keywords[10].display_name	Image processing
keywords[11].id	https://openalex.org/keywords/image
keywords[11].score	0.253638356924057
keywords[11].display_name	Image (mathematics)
keywords[12].id	https://openalex.org/keywords/algorithm
keywords[12].score	0.1677323281764984
keywords[12].display_name	Algorithm
keywords[13].id	https://openalex.org/keywords/edge-detection
keywords[13].score	0.09157824516296387
keywords[13].display_name	Edge detection
language	en
locations[0].id	doi:10.32604/cmc.2020.011006
locations[0].is_oa	True
locations[0].source.id	https://openalex.org/S4210191605
locations[0].source.issn	1546-2218, 1546-2226
locations[0].source.type	journal
locations[0].source.is_oa	True
locations[0].source.issn_l	1546-2218
locations[0].source.is_core	True
locations[0].source.is_in_doaj	False
locations[0].source.display_name	Computers, materials & continua/Computers, materials & continua (Print)
locations[0].source.host_organization
locations[0].source.host_organization_name
locations[0].license	cc-by
locations[0].pdf_url
locations[0].version	publishedVersion
locations[0].raw_type	journal-article
locations[0].license_id	https://openalex.org/licenses/cc-by
locations[0].is_accepted	True
locations[0].is_published	True
locations[0].raw_source_name	Computers, Materials & Continua
locations[0].landing_page_url	https://doi.org/10.32604/cmc.2020.011006
indexed_in	crossref
authorships[0].author.id	https://openalex.org/A5014092332
authorships[0].author.orcid	https://orcid.org/0000-0001-9287-7536
authorships[0].author.display_name	Anjie Peng
authorships[0].author_position	first
authorships[0].raw_author_name	Anjie Peng
authorships[0].is_corresponding	False
authorships[1].author.id	https://openalex.org/A5031102872
authorships[1].author.orcid	https://orcid.org/0000-0002-9734-0137
authorships[1].author.display_name	Kang Deng
authorships[1].author_position	middle
authorships[1].raw_author_name	Kang Deng
authorships[1].is_corresponding	False
authorships[2].author.id	https://openalex.org/A5057388712
authorships[2].author.orcid
authorships[2].author.display_name	Shenghai Luo
authorships[2].author_position	middle
authorships[2].raw_author_name	Shenghai Luo
authorships[2].is_corresponding	False
authorships[3].author.id	https://openalex.org/A5101708043
authorships[3].author.orcid	https://orcid.org/0000-0002-7612-8524
authorships[3].author.display_name	Hui Zeng
authorships[3].author_position	last
authorships[3].raw_author_name	Hui Zeng
authorships[3].is_corresponding	False
has_content.pdf	False
has_content.grobid_xml	False
is_paratext	False
open_access.is_oa	True
open_access.oa_url	https://doi.org/10.32604/cmc.2020.011006
open_access.oa_status	diamond
open_access.any_repository_has_fulltext	False
created_date	2025-10-10T00:00:00
display_name	Multi-Purpose Forensics of Image Manipulations Using Residual-Based Feature
has_fulltext	False
is_retracted	False
updated_date	2025-11-06T03:46:38.306776
primary_topic.id	https://openalex.org/T12357
primary_topic.field.id	https://openalex.org/fields/17
primary_topic.field.display_name	Computer Science
primary_topic.score	0.9998000264167786
primary_topic.domain.id	https://openalex.org/domains/3
primary_topic.domain.display_name	Physical Sciences
primary_topic.subfield.id	https://openalex.org/subfields/1707
primary_topic.subfield.display_name	Computer Vision and Pattern Recognition
primary_topic.display_name	Digital Media Forensic Detection
related_works	https://openalex.org/W2036807459, https://openalex.org/W2541791370, https://openalex.org/W2035976912, https://openalex.org/W2109974539, https://openalex.org/W1999222583, https://openalex.org/W1602592726, https://openalex.org/W2534909612, https://openalex.org/W2016461833, https://openalex.org/W2382607599, https://openalex.org/W3197541072
cited_by_count	4
counts_by_year[0].year	2022
counts_by_year[0].cited_by_count	1
counts_by_year[1].year	2021
counts_by_year[1].cited_by_count	3
locations_count	1
best_oa_location.id	doi:10.32604/cmc.2020.011006
best_oa_location.is_oa	True
best_oa_location.source.id	https://openalex.org/S4210191605
best_oa_location.source.issn	1546-2218, 1546-2226
best_oa_location.source.type	journal
best_oa_location.source.is_oa	True
best_oa_location.source.issn_l	1546-2218
best_oa_location.source.is_core	True
best_oa_location.source.is_in_doaj	False
best_oa_location.source.display_name	Computers, materials & continua/Computers, materials & continua (Print)
best_oa_location.source.host_organization
best_oa_location.source.host_organization_name
best_oa_location.license	cc-by
best_oa_location.pdf_url
best_oa_location.version	publishedVersion
best_oa_location.raw_type	journal-article
best_oa_location.license_id	https://openalex.org/licenses/cc-by
best_oa_location.is_accepted	True
best_oa_location.is_published	True
best_oa_location.raw_source_name	Computers, Materials & Continua
best_oa_location.landing_page_url	https://doi.org/10.32604/cmc.2020.011006
primary_location.id	doi:10.32604/cmc.2020.011006
primary_location.is_oa	True
primary_location.source.id	https://openalex.org/S4210191605
primary_location.source.issn	1546-2218, 1546-2226
primary_location.source.type	journal
primary_location.source.is_oa	True
primary_location.source.issn_l	1546-2218
primary_location.source.is_core	True
primary_location.source.is_in_doaj	False
primary_location.source.display_name	Computers, materials & continua/Computers, materials & continua (Print)
primary_location.source.host_organization
primary_location.source.host_organization_name
primary_location.license	cc-by
primary_location.pdf_url
primary_location.version	publishedVersion
primary_location.raw_type	journal-article
primary_location.license_id	https://openalex.org/licenses/cc-by
primary_location.is_accepted	True
primary_location.is_published	True
primary_location.raw_source_name	Computers, Materials & Continua
primary_location.landing_page_url	https://doi.org/10.32604/cmc.2020.011006
publication_date	2020-01-01
publication_year	2020
referenced_works_count	0
abstract_inverted_index.a	16, 62, 89, 126, 153, 157
abstract_inverted_index.In	11
abstract_inverted_index.To	45
abstract_inverted_index.an	4
abstract_inverted_index.by	50
abstract_inverted_index.in	88, 119, 182
abstract_inverted_index.is	3, 25, 71, 77, 109, 149, 174
abstract_inverted_index.of	27, 59, 128, 184
abstract_inverted_index.on	54
abstract_inverted_index.to	83, 102, 111, 155, 176
abstract_inverted_index.we	14, 94
abstract_inverted_index.The	0, 73, 145
abstract_inverted_index.and	42, 57, 99, 122, 139, 173, 187
abstract_inverted_index.can	135, 167
abstract_inverted_index.fed	151
abstract_inverted_index.for	7, 20, 141, 190
abstract_inverted_index.how	113
abstract_inverted_index.low	195
abstract_inverted_index.set	19, 134, 148
abstract_inverted_index.the	21, 47, 55, 60, 80, 104, 116, 131, 137, 142, 164, 177
abstract_inverted_index.JPEG	43, 191
abstract_inverted_index.also	95
abstract_inverted_index.both	120
abstract_inverted_index.deep	179
abstract_inverted_index.form	103
abstract_inverted_index.from	79
abstract_inverted_index.into	152
abstract_inverted_index.show	162
abstract_inverted_index.that	163
abstract_inverted_index.then	150
abstract_inverted_index.this	12
abstract_inverted_index.time	188
abstract_inverted_index.tool	6
abstract_inverted_index.used	110
abstract_inverted_index.way.	91, 124
abstract_inverted_index.with	194
abstract_inverted_index.After	125
abstract_inverted_index.forge	8
abstract_inverted_index.group	64, 82
abstract_inverted_index.image	9, 32, 52, 171, 193
abstract_inverted_index.terms	183
abstract_inverted_index.that,	93
abstract_inverted_index.train	156
abstract_inverted_index.which	24, 65, 108
abstract_inverted_index.caused	49
abstract_inverted_index.change	115
abstract_inverted_index.linear	90, 121
abstract_inverted_index.median	39
abstract_inverted_index.paper,	13
abstract_inverted_index.purely	84
abstract_inverted_index.series	127
abstract_inverted_index.Besides	92
abstract_inverted_index.capable	26
abstract_inverted_index.combine	96
abstract_inverted_index.diverse	51
abstract_inverted_index.feature	18, 107, 133, 147
abstract_inverted_index.measure	85, 112
abstract_inverted_index.methods	181
abstract_inverted_index.partial	74
abstract_inverted_index.propose	15
abstract_inverted_index.results	161
abstract_inverted_index.several	30, 67, 169
abstract_inverted_index.spatial	35
abstract_inverted_index.testing	140
abstract_inverted_index.typical	31, 170
abstract_inverted_index.Gaussian	37
abstract_inverted_index.accuracy	186
abstract_inverted_index.contains	66
abstract_inverted_index.contents	53
abstract_inverted_index.detector	166
abstract_inverted_index.feature,	61
abstract_inverted_index.filtered	69
abstract_inverted_index.highpass	68
abstract_inverted_index.identify	168
abstract_inverted_index.low-pass	36
abstract_inverted_index.proposed	105, 132, 146, 165
abstract_inverted_index.residual	63, 81
abstract_inverted_index.superior	175
abstract_inverted_index.training	138
abstract_inverted_index.CNN-based	180
abstract_inverted_index.blurring,	38
abstract_inverted_index.composite	106
abstract_inverted_index.detection	185
abstract_inverted_index.detector.	159
abstract_inverted_index.dimension	129
abstract_inverted_index.eliminate	46
abstract_inverted_index.exploited	78
abstract_inverted_index.forensics	2, 23
abstract_inverted_index.important	5
abstract_inverted_index.including	34
abstract_inverted_index.residuals	70
abstract_inverted_index.universal	17
abstract_inverted_index.accelerate	136
abstract_inverted_index.compressed	192
abstract_inverted_index.detection.	10
abstract_inverted_index.efficiency	189
abstract_inverted_index.filtering,	40
abstract_inverted_index.forensics.	144
abstract_inverted_index.influences	48
abstract_inverted_index.non-linear	123
abstract_inverted_index.robustness	58
abstract_inverted_index.transition	100
abstract_inverted_index.coefficient	76, 98
abstract_inverted_index.complicated	178
abstract_inverted_index.correlation	75
abstract_inverted_index.identifying	29
abstract_inverted_index.introduced.	72
abstract_inverted_index.probability	101
abstract_inverted_index.reductions,	130
abstract_inverted_index.resolution.	196
abstract_inverted_index.Experimental	160
abstract_inverted_index.compression.	44
abstract_inverted_index.correlations	87
abstract_inverted_index.multipurpose	143
abstract_inverted_index.neighborhood	86, 117
abstract_inverted_index.re-sampling,	41
abstract_inverted_index.effectiveness	56
abstract_inverted_index.manipulations	114
abstract_inverted_index.multi-purpose	1, 22, 158
abstract_inverted_index.relationships	118
abstract_inverted_index.autoregressive	97
abstract_inverted_index.manipulations,	33, 172
abstract_inverted_index.simultaneously	28
abstract_inverted_index.multi-classifier	154
cited_by_percentile_year.max	97
cited_by_percentile_year.min	89
countries_distinct_count	0
institutions_distinct_count	4
sustainable_development_goals[0].id	https://metadata.un.org/sdg/16
sustainable_development_goals[0].score	0.6399999856948853
sustainable_development_goals[0].display_name	Peace, Justice and strong institutions
citation_normalized_percentile.value	0.65147346
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	False