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Face Matching and Retrieval in Forensics Applications
Jain, Anil K.,Klare, Brendan,Park, Unsang IEEE 2012 IEEE multimedia Vol.19 No.1
<P>This article surveys forensic face-recognition approaches and the challenges they face in improving matching and retrieval results as well as processing low-quality images.</P>
Soft Biometric Traits for Continuous User Authentication
Niinuma, Koichiro,Unsang Park,Jain, Anil K IEEE 2010 IEEE transactions on information forensics and sec Vol.5 No.4
<P>Most existing computer and network systems authenticate a user only at the initial login session. This could be a critical security weakness, especially for high-security systems because it enables an impostor to access the system resources until the initial user logs out. This situation is encountered when the logged in user takes a short break without logging out or an impostor coerces the valid user to allow access to the system. To address this security flaw, we propose a continuous authentication scheme that continuously monitors and authenticates the logged in user. Previous methods for continuous authentication primarily used hard biometric traits, specifically fingerprint and face to continuously authenticate the initial logged in user. However, the use of these biometric traits is not only inconvenient to the user, but is also not always feasible due to the user's posture in front of the sensor. To mitigate this problem, we propose a new framework for continuous user authentication that primarily uses soft biometric traits (e.g., color of user's clothing and facial skin). The proposed framework automatically registers (enrolls) soft biometric traits every time the user logs in and fuses soft biometric matching with the conventional authentication schemes, namely password and face biometric. The proposed scheme has high tolerance to the user's posture in front of the computer system. Experimental results show the effectiveness of the proposed method for continuous user authentication.</P>
Restoring Degraded Face Images: A Case Study in Matching Faxed, Printed, and Scanned Photos
Bourlai, Thirimachos,Ross, Arun,Jain, Anil K IEEE 2011 IEEE transactions on information forensics and sec Vol.6 No.2
<P>We study the problem of restoring severely degraded face images such as images scanned from passport photos or images subjected to fax compression, downscaling, and printing. The purpose of this paper is to illustrate the complexity of face recognition in such realistic scenarios and to provide a viable solution to it. The contributions of this work are two-fold. First, a database of face images is assembled and used to illustrate the challenges associated with matching severely degraded face images. Second, a preprocessing scheme with low computational complexity is developed in order to eliminate the noise present in degraded images and restore their quality. An extensive experimental study is performed to establish that the proposed restoration scheme improves the quality of the ensuing face images while simultaneously improving the performance of face matching.</P>
Heterogeneous Face Recognition Using Kernel Prototype Similarities
Klare, Brendan F.,Jain, Anil K. IEEE 2013 IEEE transactions on pattern analysis and machine Vol.35 No.6
<P>Heterogeneous face recognition (HFR) involves matching two face images from alternate imaging modalities, such as an infrared image to a photograph or a sketch to a photograph. Accurate HFR systems are of great value in various applications (e.g., forensics and surveillance), where the gallery databases are populated with photographs (e.g., mug shot or passport photographs) but the probe images are often limited to some alternate modality. A generic HFR framework is proposed in which both probe and gallery images are represented in terms of nonlinear similarities to a collection of prototype face images. The prototype subjects (i.e., the training set) have an image in each modality (probe and gallery), and the similarity of an image is measured against the prototype images from the corresponding modality. The accuracy of this nonlinear prototype representation is improved by projecting the features into a linear discriminant subspace. Random sampling is introduced into the HFR framework to better handle challenges arising from the small sample size problem. The merits of the proposed approach, called prototype random subspace (P-RS), are demonstrated on four different heterogeneous scenarios: 1) near infrared (NIR) to photograph, 2) thermal to photograph, 3) viewed sketch to photograph, and 4) forensic sketch to photograph.</P>
Multibiometric Cryptosystems Based on Feature-Level Fusion
Nagar, Abhishek,Nandakumar, Karthik,Jain, Anil K. IEEE 2012 IEEE transactions on information forensics and sec Vol.7 No.1
<P>Multibiometric systems are being increasingly de- ployed in many large-scale biometric applications (e.g., FBI-IAFIS, UIDAI system in India) because they have several advantages such as lower error rates and larger population coverage compared to unibiometric systems. However, multibiometric systems require storage of multiple biometric templates (e.g., fingerprint, iris, and face) for each user, which results in increased risk to user privacy and system security. One method to protect individual templates is to store only the secure sketch generated from the corresponding template using a biometric cryptosystem. This requires storage of multiple sketches. In this paper, we propose a feature-level fusion framework to simultaneously protect multiple templates of a user as a single secure sketch. Our main contributions include: (1) practical implementation of the proposed feature-level fusion framework using two well-known biometric cryptosystems, namery,fuzzy vault and fuzzy commitment, and (2) detailed analysis of the trade-off between matching accuracy and security in the proposed multibiometric cryptosystems based on two different databases (one real and one virtual multimodal database), each containing the three most popular biometric modalities, namely, fingerprint, iris, and face. Experimental results show that both the multibiometric cryptosystems proposed here have higher security and matching performance compared to their unibiometric counterparts.</P>
Robust Keypoint Detection Using Higher-Order Scale Space Derivatives: Application to Image Retrieval
Unsang Park,Jongseung Park,Jain, Anil K. IEEE Signal Processing Society 2014 IEEE signal processing letters Vol. No.
<P>Image retrieval has been extensively studied over the last two decades due to the increasing demands for the effective use of multimedia data. Among various approaches to image retrieval, scale space representation and local keypoint descriptors have been shown to be a promising approach. Even though the concept of scale space representation has been known for a long time, it has now gained prominence as a powerful method for image retrieval mostly due to the invention of the Scale Invariant Feature Transform (SIFT). We will review the characteristics of the scale space operation and provide an extended method of scale space operation that significantly improves the image matching accuracy in the context of image retrieval. We use an operational tattoo image database containing 1,000 near duplicate images to show the superior retrieval performance of the proposed method compared to SIFT keypoints.</P>
Polyurethane 표면처리 목재에서 잠재지문 현출
최용복,박원석,류일녕,성낙도,박성우,Anil K. Jain 한국과학수사학회 2011 과학수사학회지 Vol.5 No.2
본 연구는 살인사건 현장에서 감식 중 여러 가지 증거물을 찾는 과정에서 식탁 위에 유류되어있는 잠재 지문에 대하여 형광분말을 사용하여 현출시켜 용의자의 신원에 대한 개인식별을 할 수 있었던 사안으로 현장보존과 현장조사(감식)를 철저히 하여야만 사건해결에 필요한 결정적인 증거물을 채취, 용의자를 특정한 후 검거하여 유죄의 증거로 사용할 수 있다는 점과 사례에서 지문을 유류시켰던 탁자 (식탁)의 나무 재질 검체에서는 일반 분말을 사용하는 것 보다도 형광분말을 사용하여 잠재지문을 현출 시키는 것이 효율적임을 실제사례와 실험을 통하여 재 입증한 후 이를 실무에 적용하고자 하였던 연구이다. 앞으로 본 연구를 바탕으로 같은 종류의 검체에서는 본 연구 자료를 활용함과 동시에 현장에서 발견되는 새로운 많은 검체들에 대하여는 각 종류별로 지속적인 실험과 연구를 통하여 어떤 방법이 더 효율적인가를 찾아 실무에 적용하여야 할 것이다.