36496685
Segmentation-free printed character recognition by relaxed nearest neighbor learning of windowed operator
Segmentation is considered by many researchers as the key technology for a reliable optical character recognition (OCR) system. To accomplish sound segmentation, many alternative techniques have been recently proposed. This paper presents a new technique to recognize characters without explicit segmentation. It is based on the automatic construction of a windowed operator by relaxed nearest neighbor learning. It has been implemented, tested and yielded excellent recognition accuracy and computational performance.
4790058
A public-key authentication watermarking for binary images
Authentication watermarking is the process that inserts hidden data into an object (image) in order to detect any fraudulent alteration perpetrated by a malicious hacker. In the literature, quite a small number of secure authentication methods are available for binary images. This paper proposes a new secure authentication watermarking method for binary images. It can detect any visually significant alteration while maintaining good visual quality. As usual, the security of the algorithm lies on the secrecy of a private-key. Only its owner can insert the correct watermark while anyone may verify the authenticity through the corresponding public-key. A possible application of the proposed technique is in Internet fax transmission, i.e. for legal authentication of documents routed outside the phone network.
13935279
Robust anisotropic diffusion to produce clear statistical parametric map from noisy fMRI
Functional magnetic resonance imaging (fMRI) uses MRI to noninvasively map areas of increased neuronal activity in human brain without the use of an exogenous contrast agent. Low signal-to-noise ratio of fMRI images makes it necessary to use sophisticated image processing techniques, such as statistical parametric map (SPM), to detect activated brain areas. This paper presents a new technique to obtain clear SPM from noisy fMRI data. It is based on the robust anisotropic diffusion. A direct application of the anisotropic diffusion to fMRI does not work, mainly due to the lack of sharp boundaries between activated and non-activated regions. To overcome this difficulty, we propose to calculate SPM from noisy fMRI, compute diffusion coefficients in the SPM space, and then perform the diffusion in fMRI images using the coefficients previously computed. These steps are iterated until the convergence. Experimental results using the new technique yielded surprisingly sharp and noiseless SPMs.
3147895
Pitfalls in public key watermarking
The cryptographic concept of digital signatures is well suited to image watermarking for authentication and integrity verification. However, the peculiar nature of watermarks demands special care in the application of digital signatures for this purpose. We cryptanalyze a recently proposed watermarking scheme and show how it can be strengthened to thwart our attacks, exploring the use of hashing function contexts and signature algorithms based on elliptic curve cryptography.
15509328
New features for affine-invariant shape classification
An object seen from different viewpoints results in differently deformed images. Affine-invariant shape classification must classify correctly the object, regardless its viewpoint. In this paper, we propose new local and global features invariant under affine transformation. These features can be used for supervised or unsupervised shape classification, and for shape-based image indexing and retrieval. One of the proposed features is related to the convex deficiency and the others are extracted from the area matrix. Area matrix was used by Shen for the similarity matching in image retrieval. However, differently from the Shen's work, we parameterize the shape contour using the affine-length parameter. This makes our features robust to affine parameterization, while Shen's work does not have this property. Experimental results indicate that our method can classify correctly even highly deformed and noisy shapes using small training sets.
6853667
Efficient Algorithms for Pairing-Based Cryptosystems
We describe fast new algorithms to implement recent cryptosystems based on the Tate pairing. In particular, our techniques improve pairing evaluation speed by a factor of about 55 compared to previously known methods in characteristic 3, and attain performance comparable to that of RSA in larger characteristics. We also propose faster algorithms for scalar multiplication in characteristic 3 and square root extraction over Fpm, the latter technique being also useful in contexts other than that of pairing-based cryptography.
4633793
Independent component analysis in a local facial residue space for face recognition
In this paper, we propose an Independent Component Analysis (ICA) based face recognition algorithm, which is robust to illumination andpose variation. Generally, it is well known that the 5rst few eigenfaces represent illumination variation rather than identity. Most Principal Component Analysis (PCA) based methods have overcome illumination variation by discarding the projection to a few leading eigenfaces. The space spanned after removing a few leading eigenfaces is called the “residual face space”. We found that ICA in the residual face space provides more e9cient encoding in terms of redundancy reduction androbustness to pose variation as well as illumination variation, owing to its ability to represent non-Gaussian statistics. Moreover, a face image is separatedinto several facial components, local spaces, andeach local space is representedby the ICA bases (independent components) of its corresponding residual space. The statistical models of face images in local spaces are relatively simple andfacilitate classi5cation by a linear encoding. Various experimental results show that the accuracy of face recognition is signi5cantly improvedby the proposedmethodunder large illumination andpose variations.
33400437
Facial Expression Recognition Using Active Appearance Model
This paper describes a facial expression recognition system based upon Active Appearance Model (AAM), which has been typically used for the face recognition task. Given that AAM has been also used in tracking the moving object, we thought it could be effective in recognizing the facial expressions of humans. Our results show that the performance of the facial expression recognition using AAM is reliably high when it combined with an enhanced Fisher classification model.
6043201
MOQ: Web services ontologies for QoS and general quality evaluations
When describing web services, one of the obvious aspects that need representing is 'Quality of Service' (QoS), the capability of a web service to meet an acceptable level of service as per factors such as availability and accessibility. However, too much of a focus on developing functional QoS ontologies has led to an over-emphasis on representing solely QoS metrics and units of measurement. For instance, what does round trip time actually mean? Is the round trip time of every data item measured? Is it an average, or is every nth item measured? Is it the actual measure that is important or just the percentage of items that are beyond a certain range? Arguably existing QoS ontologies cannot readily answer many of these design questions because these questions have less to do with evaluating QoS and more to do with representing 'what is quality?' Therefore, there is an unmet need for web services ontologies that are designed at a higher level encompassing domain independent concepts, and generally applicable beyond QoS evaluations. The MOQ set of ontologies, designed from the premise that quality is 'conformance to requirements', aims to fill this need. Comprised of ontologies of requirement, measurement, traceability, and quality management systems, MOQ can be extended to encompass QoS metrics and measurement units or be designed to interoperate with existing QoS ontology. The use of MOQ minimises the ambiguity in QoS evaluations.
8273227
Mapping from BPMN-Formed Business Processes to XPDL Business Processes
In the business process management, many business process execution languages such as XPDL, BPML, BPEL4WS have been specified with different origins and goals. Most of all, XPDL proposed by WfMC has been widely used in the related applications, especially workflows whose concepts are currently interchangeable with those of business processes. On the other hand, Business Process Modeling Notation (BPMN) driven by BPMI has recently been specified as a standardized graphical notation for a business process. We can therefore commonly design and analyze various business processes using the design tools to support BPMN. Notice that a BPMN-formed business process should be converted to its semantically equivalent business process languages such as XPDL which can consequently be executed by business process engines. In this regard, we propose a transformation mechanism from BPMN-formed business processes to corresponding XPDL processes.
8295029
Cache filtering techniques to reduce the negative impact of useless speculative memory references on processor performance
High-performance processors employ aggressive speculation and prefetching techniques to increase performance. Speculative memory references caused by these techniques sometimes bring data into the caches that are not needed by correct execution. This paper proposes the use of the first-level caches as filters that predict the usefulness of speculative memory references. With the proposed technique, speculative memory references bring data only into the first-level caches rather than all levels in the cache hierarchy. The processor monitors the use of the cache blocks in the first-level caches and decides which blocks to keep in the cache hierarchy based on the usefulness of cache blocks. It is shown that a simple implementation of this technique usually outperforms inclusive and exclusive baseline cache hierarchies commonly used by today's processors and results in IPC performance improvements of up to 9.2% on the SPEC2000 integer benchmarks.