Steganographic methods usually produce distortions in cover images due to the process of embedding secret bits. These distortions are hard to remove, and thus the cover image cannot be recovered. Although the distortions are always small, they cannot be allowed for some sensitive applications. In this paper, we propose a reversible embedding scheme for VQ-compressed images, which allows the original cover image to be completely recovered after the extraction of the secret bits. The embedded payload in the proposed method comprises the secret bits plus the restoration information. In order to reduce the size of payload, we utilized the spatial correlations in the image as the restoration information and then compressed the correlations by a lossless compression method. In addition, an alternative pairing method for codewords was proposed to improve the stegoed image quality and control the embedding capacity. Experimental results showed that the proposed method has the benefit of high efficiency of the steganographic process, high image quality, and adaptive embedding capacity compared with other schemes.

In recent decades, there has been a great deal of research into the problem of bilingual speech recognition - to develop a recognizer that can handle inter- and intra-sentential language switching between two languages. This paper presents our recent work on the development of a grammar-constrained, Mandarin-English bilingual Speech Recognition System (MESRS) for real world music retrieval. Two of the main difficult issues in handling the bilingual speech recognition systems for real world applications are tackled in this paper. One is to balance the performance and the complexity of the bilingual speech recognition system; the other is to effectively deal with the matrix language accents in embedded language. In order to process the intra-sentential language switching and reduce the amount of data required to robustly estimate statistical models, a compact single set of bilingual acoustic models derived by phone set merging and clustering is developed instead of using two separate monolingual models for each language. In our study, a novel Two-pass phone clustering method based on Confusion Matrix (TCM) is presented and compared with the log-likelihood measure method. Experiments testify that TCM can achieve better performance. Since potential system users' native language is Mandarin which is regarded as a matrix language in our application, their pronunciations of English as the embedded language usually contain Mandarin accents. In order to deal with the matrix language accents in embedded language, different non-native adaptation approaches are investigated. Experiments show that model retraining method outperforms the other common adaptation methods such as Maximum A Posteriori (MAP). With the effective incorporation of approaches on phone clustering and non-native adaptation, the Phrase Error Rate (PER) of MESRS for English utterances was reduced by 24.47% relatively compared to the baseline monolingual English system while the PER on Mandarin utterances was comparable to that of the baseline monolingual Mandarin system. The performance for bilingual utterances achieved 22.37% relative PER reduction.

This paper presents a lossless steganography method based on the multiple-base notation approach for JPEG images. Embedding a large amount of secret data in a JPEG-compressed image is a challenge since modifying the quantized DCT coefficients may cause serious image distortion. We propose two main strategies to deal with this problem: (1) we embed the secret values in the middle-frequency of the quantized DCT coefficients, and (2) we limit the number of nonzero values of the quantized DCT coefficients that participate in the embedding process. We also investigated the effect of modifying the standard quantization table. The experimental results show that the proposed method can embed twice as much secret data as the irreversible embedding method of Iwata et al. under the same number of embedded sets. The results also demonstrate how three important factors: (1) the quantization table, (2) the number of selected nonzero quantized DCT coefficients, and (3) the number of selected sets, influence the image quality and embedding capacity.

This paper is aimed to present the design and feasibility investigations of adopting the available on-site optical inspection system, which is commonly used for steel plate dimension measurement, to supply on-line dynamic gap measurements of a non-contacting conveyance structure in a steel mill. Adequate software and hardware implementations based on digital image processing techniques have been adapted to the entire system formulations and estimations. Results show that the system can supply accurate and rapid gap measurements and thus can fulfill the design and operational objectives.

With more digital home appliances and network devices having OSGi as the software management platform, the power-saving capability of the OSGi platform has become a critical issue. This paper is aimed at improving the power-efficiency of the OSGi platform, i.e. reducing the energy consumption with minimum performance degradation. The key to this study is an efficient power-saving technique which exploits the runtime information already available in a Java virtual machine (JVM), the base software of the OSGi platform, to best determine the timing of performing DVFS (Dynamic Voltage and Frequency Scaling). This, technically, involves a phase detection scheme that identifies the memory phase of the OSGi-enabled device/server in a correct and almost effortless way. The overhead of the power-saving procedure is thus minimized, and the system performance is well maintained. We have implemented and evaluated the proposed power-saving approach on an OSGi server, where the Apache Felix OSGi implementation and the DaCapo benchmarks were applied. The results show that this approach can achieve real power-efficiency for the OSGi platform, in which the power consumption is significantly reduced and the performance remains highly competitive, compared with the other power-saving techniques.