IEEE Signal Processing Magazine Journal Impact Factor & Information

Publisher: Institute of Electrical and Electronics Engineers; IEEE Signal Processing Society, Institute of Electrical and Electronics Engineers

Journal description

The practical applications aspects of acoustics, speech, and signal processing.

Current impact factor: 4.48

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2013 / 2014 Impact Factor 4.481
2012 Impact Factor 3.368
2011 Impact Factor 4.066
2010 Impact Factor 5.86
2009 Impact Factor 4.914
2008 Impact Factor 3.758
2007 Impact Factor 2.907
2006 Impact Factor 2.655
2005 Impact Factor 2.714
2004 Impact Factor 3.707
2003 Impact Factor 4.241
2002 Impact Factor 3.298
2001 Impact Factor 1.981
2000 Impact Factor 1.185
1999 Impact Factor 2.256
1998 Impact Factor 1.879
1997 Impact Factor 0.943

Impact factor over time

Impact factor

Additional details

5-year impact 6.90
Cited half-life 6.30
Immediacy index 0.22
Eigenfactor 0.02
Article influence 3.56
Website IEEE Signal Processing Magazine website
Other titles IEEE signal processing magazine, Institute of Electrical and Electronics Engineers signal processing magazine, Signal processing magazine, I.E.E.E. signal processing magazine, IEEE SP magazine
ISSN 1053-5888
OCLC 22582650
Material type Periodical, Internet resource
Document type Journal / Magazine / Newspaper, Internet Resource

Publisher details

Institute of Electrical and Electronics Engineers

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Author's pre-print on Author's personal website, employers website or publicly accessible server
    • Author's post-print on Author's server or Institutional server
    • Author's pre-print must be removed upon publication of final version and replaced with either full citation to IEEE work with a Digital Object Identifier or link to article abstract in IEEE Xplore or replaced with Authors post-print
    • Author's pre-print must be accompanied with set-phrase, once submitted to IEEE for publication ("This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible")
    • Author's pre-print must be accompanied with set-phrase, when accepted by IEEE for publication ("(c) 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.")
    • IEEE must be informed as to the electronic address of the pre-print
    • If funding rules apply authors may post Author's post-print version in funder's designated repository
    • Author's Post-print - Publisher copyright and source must be acknowledged with citation (see above set statement)
    • Author's Post-print - Must link to publisher version with DOI
    • Publisher's version/PDF cannot be used
    • Publisher copyright and source must be acknowledged
  • Classification
    ‚Äč green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Biometric recognition is an integral component of modern identity management and access control systems. Due to the strong and permanent link between individuals and their biometric traits, exposure of enrolled users? biometric information to adversaries can seriously compromise biometric system security and user privacy. Numerous techniques have been proposed for biometric template protection over the last 20 years. While these techniques are theoretically sound, they seldom guarantee the desired noninvertibility, revocability, and nonlinkability properties without significantly degrading the recognition performance. The objective of this work is to analyze the factors contributing to this performance divide and highlight promising research directions to bridge this gap. The design of invariant biometric representations remains a fundamental problem, despite recent attempts to address this issue through feature adaptation schemes. The difficulty in estimating the statistical distribution of biometric features not only hinders the development of better template protection algorithms but also diminishes the ability to quantify the noninvertibility and nonlinkability of existing algorithms. Finally, achieving nonlinkability without the use of external secrets (e.g., passwords) continues to be a challenging proposition. Further research on the above issues is required to cross the chasm between theory and practice in biometric ?template protection.
    IEEE Signal Processing Magazine 09/2015; 32(5):88-100. DOI:10.1109/MSP.2015.2427849
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    ABSTRACT: Recent years have seen an exponential growth in the use of various biometric technologies for trusted automatic recognition of humans. With the rapid adaptation of biometric systems, there is a growing concern that biometric technologies may compromise the privacy and anonymity of individuals. Unlike credit cards and passwords, which can be revoked and reissued when compromised, biometrics are permanently associated with a user and cannot be replaced. To prevent the theft of biometric patterns, it is desirable to modify them through revocable and noninvertible transformations to produce cancelable biometric templates. In this article, we provide an overview of various cancelable biometric schemes for biometric template protection. We discuss the merits and drawbacks of available cancelable biometric systems and identify promising avenues of research in this rapidly evolving field.
    IEEE Signal Processing Magazine 09/2015; 32(5):54-65. DOI:10.1109/MSP.2015.2434151
  • [Show abstract] [Hide abstract]
    ABSTRACT: Biometrics refers to physiological (i.e., face, fingerprint, hand geometry, etc.) and behavioral (i.e., speech, signature, keystroke, etc.) traits of a human identity. As these traits are unique to individuals, biometrics can be used to identify users reliably in many authentication applications, such as access control and e-commerce. Most biometric authentication systems offer great convenience without requiring the users to possess or remember any secret credentials. For applications that demand greater security, biometrics can be used in complement with passwords and security tokens to offer a multifactor authentication.
    IEEE Signal Processing Magazine 09/2015; 32(5):77-87. DOI:10.1109/MSP.2015.2423693
  • [Show abstract] [Hide abstract]
    ABSTRACT: Biometrics already form a significant component of current and emerging identification technologies. Biometrics systems aim to determine or verify the identity of an individual from their behavioral and/or biological characteristics. Despite significant progress, some biometric systems fail to meet the multitude of stringent security and robustness requirements to support their deployment in some practical scenarios. Among current concerns are vulnerabilities to spoofing?persons who masquerade as others to gain illegitimate accesses to protected data, services, or facilities. While the study of spoofing, or rather antispoofing, has attracted growing interest in recent years, the problem is far from being solved and will require far greater attention in the coming years. This tutorial article presents an introduction to spoofing and antispoofing research. It describes the vulnerabilities, presents an evaluation methodology for the assessment of spoofing and countermeasures, and outlines research priorities for the future.
    IEEE Signal Processing Magazine 09/2015; 32(5):20-30. DOI:10.1109/MSP.2015.2437652
  • [Show abstract] [Hide abstract]
    ABSTRACT: The importance of signal processing in imaging is growing rapidly as technologies continue to develop and mature and as various fields begin to recognize the value of innovative new imaging and image analysis systems. By enabling people to clearly observe and detect things that are not ordinarily visible or not readily apparent to the unaided eye, signal processing-driven imaging technologies are helping to save lives and property from hazards lurking both on the ground and below the earth?s surface.
    IEEE Signal Processing Magazine 09/2015; 32(5):8-18. DOI:10.1109/MSP.2015.2437291
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    ABSTRACT: Biometric systems provide a valuable service in helping to identify individuals from their stored personal details. Unfortunately, with the rapidly increasing use of such systems [1], there is a growing concern about the possible misuse of that information. To counteract the threat, the European Union (EU) has introduced comprehensive legislation [2] that seeks to regulate data collection and help strengthen an individual?s right to privacy. This article looks at the implications of the legislation for biometric system deployment. After an initial consideration of current privacy concerns, the definition of ?personal data? and its protection is examined in legislative terms. Also covered are the issues surrounding the storage of biometric data, including its accuracy, its security, and justification for what is collected. Finally, the privacy issues are illustrated through three biometric use cases: border security, online bank access control, and customer profiling in stores.
    IEEE Signal Processing Magazine 09/2015; 32(5):101-108. DOI:10.1109/MSP.2015.2426682
  • [Show abstract] [Hide abstract]
    ABSTRACT: Presents the President's Message for this issue of the publication regarding the adoption of new peer-review models for research papers.
    IEEE Signal Processing Magazine 09/2015; 32(5):6-6. DOI:10.1109/MSP.2015.2449286
  • [Show abstract] [Hide abstract]
    ABSTRACT: The articles in this special section were conceived to champion recent developments in the rapidly evolving field of biometrics and also to encourage research in new signal processing solutions to security and privacy protection. Biometrics is the science of recognizing individuals based on their behavioral and biological characteristics such as face, fingerprints, iris, voice, gait, and signature. The past decade has witnessed a rapid increase in biometrics research in addition to the deployment of large-scale biometrics solutions in both civilian and law enforcement applications. Example applications that incorporate biometric recognition include: logical and physical access systems; surveillance operations to fight against fraud and organized crime; immigration control and border security systems; national identity programs; identity management systems; and the determination of friend or foe in military installations.
    IEEE Signal Processing Magazine 09/2015; 32(5):17-18. DOI:10.1109/MSP.2015.2443271
  • [Show abstract] [Hide abstract]
    ABSTRACT: Biometrics were originally developed for identification, such as for criminal investigations. More recently, biometrics have been also utilized for authentication. Most biometric authentication systems today match a user?s biometric reading against a stored reference template generated during enrollment. If the reading and the template are sufficiently close, the authentication is considered successful and the user is authorized to access protected resources. This binary matching approach has major inherent vulnerabilities.
    IEEE Signal Processing Magazine 09/2015; 32(5):42-53. DOI:10.1109/MSP.2015.2439717
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    ABSTRACT: Presents an historical account of the Abbey Road recording studios in England where the Beatles recorded their music. Abbey Road Studios have been an iconic landmark in London ever since The Beatles decided to name their latest album according to the street where their recording studio was located???and illustrate its cover with its now-famous pedestrian crossing. However, on 1 April 2015, there was another kind of success celebrated there. A new IEEE Historic Milestone plaque has been unveiled to commemorate the numerous inventions of engineer Alan Dower Blumlein on stereo sound recording and reproduction. Reports on this event.
    IEEE Signal Processing Magazine 09/2015; 32(5):14-16. DOI:10.1109/MSP.2015.2440191
  • [Show abstract] [Hide abstract]
    ABSTRACT: An article by W.L. Everitt in the 1962 50th anniversary issue of Proceedings of the IEEE, ?Engineering Education?Circa 2012 A.D.,? was one of many predictive articles that appeared in that issue [1]. One of Everitt?s observations was the distinction between training and education. He then predicted that, in the future, training will be done primarily with computers, remarking, ?Relieved of the necessity of spending most of their time on the training function, devoted teachers will be able to concentrate their efforts on ?education?.?
    IEEE Signal Processing Magazine 09/2015; 32(5):112-118. DOI:10.1109/MSP.2015.2438992
  • [Show abstract] [Hide abstract]
    ABSTRACT: Signal processing is the key to success for the efficient storage, transmission, and manipulation of information. The liveliness of signal processing relies on having a large number of students who undertake this research and embark on this career path. Signal processing is part of the curriculum in many undergraduate engineering programs. Some of the students also do their capstone or final-year projects on signal processing. To increase students? interest in signal processing and to get them to better appreciate its applications in real life, the IEEE Signal Processing Society (SPS) has created an undergraduate competition, referred to as the Signal Processing Cup (SP Cup) [1], which provides undergraduate students with an opportunity to form teams and work together to solve a challenging and interesting real-world problem using signal processing techniques and methods. The first competition was held at the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2014. Based on its success, it has now been instated as an annual event at ICASSP conferences.
    IEEE Signal Processing Magazine 07/2015; 32(4):123-125. DOI:10.1109/MSP.2015.2419291
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    ABSTRACT: The author announces the creation of the Signal Processing Repository (SigPort), an online repository of manuscripts, reports, technical white papers, theses, and supporting materials. Created and supported by the IEEE Signal Processing Society (SPS), SigPort collects technical material of interest to the broad signal and information processing community, with categories covering each of the Society's technical committees. Much like arXiv, SigPort hosts material to help individuals obtain early and broad exposure to their work. SigPort provides a time stamp for each uploaded document; a unique URL is assigned to the document, designating it as part of the IEEE SPS SigPort as well as for easy referencing. Also similar to arXiv, SigPort papers are not peer reviewed. Authors retain all the rights to their documents and can submit them later to journals, conferences, books, etc., since submissions to the SigPort repository are not as restricted as formal publications. We expect a majority of the e-prints to be submitted to one of the Society's journals for publication, but some works may remain purely as eprints and will never be published in a peer-reviewed journal. SigPort documents can be accessed for free at
    IEEE Signal Processing Magazine 07/2015; 32(4):6-6. DOI:10.1109/MSP.2015.2425152
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    ABSTRACT: Texture characterization of photographic prints can provide scholars with valuable information regarding photographers? aesthetic intentions and working practices. Currently, texture assessment is strictly based on the visual acuity of a range of scholars associated with collecting institutions, such as museum curators and conservators. Natural interindividual discrepancies, intraindividual variability, and the large size of collections present a pressing need for computerized and automated solutions for the texture characterization and classification of photographic prints. In the this article, this challenging image processing task is addressed using an anisotropic multiscale representation of texture, the hyperbolic wavelet transform (HWT), from which robust multiscale features are constructed. Cepstral distances aimed at ensuring balanced multiscale contributions are computed between pairs of images. The resulting large-size affinity matrix is then clustered using spectral clustering, followed by a Ward linkage procedure. For proof of concept, these procedures are first applied to a reference data set of historic photographic papers that combine several levels of similarity and second to a large data set of culturally valuable photographic prints held by the Museum of Modern Art in New York. The characterization and clustering results are interpreted in collaboration with art scholars with an aim toward developing new modes of art historical research and humanities-based collaboration.
    IEEE Signal Processing Magazine 07/2015; 32(4):18-27. DOI:10.1109/MSP.2015.2402056
  • IEEE Signal Processing Magazine 07/2015; 32(4):4-4. DOI:10.1109/MSP.2015.2425151
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    ABSTRACT: The High Efficiency Image File Format (HEIF) is a standard developed by the Moving Picture Experts Group (MPEG) for the storage of images and image sequences. The standard facilitates file encapsulation of data coded according to the High Efficiency Video Coding (HEVC) standard. The compression performance of HEVC is superior to any alternative image or image sequence coding format. HEIF includes a rich set of features building on top of the widely used ISO Base Media File Format (ISOBMFF), making HEIF superior feature-wise compared to other image file formats. This article provides an overview of the performance, features, and design of HEIF.
    IEEE Signal Processing Magazine 07/2015; 32(4):150-156. DOI:10.1109/MSP.2015.2419292
  • [Show abstract] [Hide abstract]
    ABSTRACT: This article presents an integrated framework for multimedia access and analysis of ancient Maya epigraphic resources, which is developed as an interdisciplinary effort involving epigraphers (someone who deciphers ancient inscriptions) and computer scientists. Our work includes several contributions: a definition of consistent conventions to generate high-quality representations of Maya hieroglyphs from the three most valuable ancient codices, which currently reside in European museums and institutions; a digital repository system for glyph annotation and management; as well as automatic glyph retrieval and classification methods. We study the combination of statistical Maya language models and shape representation within a hieroglyph retrieval system, the impact of applying language models extracted from different hieroglyphic resources on various data types, and the effect of shape representation choices for glyph classification. A novel Maya hieroglyph data set is given, which can be used for shape analysis benchmarks, and also to study the ancient Maya writing system.
    IEEE Signal Processing Magazine 07/2015; 32(4):75-84. DOI:10.1109/MSP.2015.2411291