14734990
Reversible data-embedding with a hierarchical structure
Reversible data-embedding embeds data into a digital content (such as digital image, audio or video) such that an authorized party could decode the embedded data and completely restore the original content. In this paper, we present a hierarchically structured, multi-layer algorithm for digital images. Its basic component is an invertible sharpen filter called the difference expansion. The embedding capacity of this algorithm is substantially higher than results reported in previous reversible data-embedding algorithms. The visual quality of images after data-embedding is also among the best in the literature.
6315327
Reversible data embedding using a difference expansion
Reversible data embedding has drawn lots of interest recently. Being reversible, the original digital content can be completely restored. We present a novel reversible data-embedding method for digital images. We explore the redundancy in digital images to achieve very high embedding capacity, and keep the distortion low.
25090129
Comments on "A translation- and scale-invariant adaptive wavelet transform"
Xiong et al. presented a translationand scale-invariant adaptive wavelet transform. We show that their renormalized signal (pre-wavelet transform) is already translation- and scale-invariant. Thus, it is not just invariant under the wavelet transform. We give a necessary and sufficient condition for renormalized signals to be affine transform invariant.
39882874
A comparison of measurement and defect characteristics of new and legacy software systems
Abstract This paper compares the quality characteristics of a large legacy software system and a new one. Defect fixes applied to specific modules during testing are used as the direct quality metric. Indirect quality indicators used in this paper include software metrics of various product and process attributes, including design, size, change, and complexity. We analyze and compare the measurement results by examining their individual distributions, the correlations between defects and quality indicators, and tree-based models linking defects to quality indicators. In both these systems, most of the defects are found to be concentrated on relatively few high-defect modules, which points to the need for appropriate risk identification techniques so that defect removal effort can be focused on those high-defect modules for effective quality improvement. In addition, defects in the legacy system are more closely related to change and data complexity metrics; while defects in the new system are more closely related to various design metrics. These results demonstrate different measurement characteristics for these two types of software systems, and suggest that different quality analysis and improvement methods may be more appropriate and effective for different kinds of software systems.
46034477
Reliability Measurement, Analysis, and Improvement for Large Software Systems
Abstracts This chapter surveys recent developments in software reliability engineering, and presents results in measuring test activities, analyzing product reliability, and identifying high risk areas for focused reliability improvement for large software systems. Environmental constraints and existing analysis techniques are carefully examined to select appropriate analysis techniques, models, implementation strategies, and support tools suitable for large software systems. The analysis and modeling activities include measure definition, data gathering, graphical test activity and defect tracking, overall quality assessment using software reliability growth models, and identification of problematic areas and risk management using tree-based reliability models. Various existing software tools have been adapted and integrated to support these analysis and modeling activities. This approach has been used in the testing phase of several large software products developed in the IBM Software Solutions Toronto Laboratory and was demon- strated to be effective and efficient. Various practical problems and solutions in implementing this strategy are also discussed.
19924236
Test-Execution-Based Reliability Measurement and Modeling for Large Commercial Software
The paper studies practical reliability measurement and modeling for large commercial software systems based on test execution data collected during system testing. The application environment and the goals of reliability assessment were analyzed to identify appropriate measurement data. Various reliability growth models were used on failure data normalized by test case executions to track testing progress and provide reliability assessment. Practical problems in data collection, reliability measurement and modeling, and modeling result analysis were also examined. The results demonstrated the feasibility of reliability measurement in a large commercial software development environment and provided a practical comparison of various reliability measurements and models under such an environment. >
46662719
A minutiae matching algorithm in fingerprint verification
Fingerprint matching is one of the most important problems in AFIS. In general, we use minutiae such as ridge endings and ridge bifurcation to represent a fingerprint and do fingerprint matching through minutiae matching. We propose a minutiae matching algorithm which modified Jain et al.'s algorithm (1997). Our algorithm can better distinguish two images from different fingers and is more robust to nonlinear deformation. Experiments done on a set of fingerprint images captured with an inkless scanner shows that our algorithm is fast and has high accuracy.
393156
A general identification condition for causal effects
This paper concerns the assessment of the effects of actions or policy interventions from a combination of: (i) nonexperimental data, and (ii) substantive assumptions. The assumptions are encoded in the form of a directed acyclic graph, also called "causal graph", in which some variables are presumed to be unobserved. The paper establishes a necessary and sufficient criterion for the identifiability of the causal effects of a singleton variable on all other variables in the model, and a powerful sufficient criterion for the effects of a singleton variable on any set of variables.