The paper presents an smoke-detection method for early fire-alarming system based on video processing. The basic strategy of smoke-pixel judgment is composed of two decision rules: a chromaticity-based static decision rule and a diffusion-based dynamic characteristic decision rule. The chromatic decision rule is deduced by grayish color of smoke and dynamic decision rule is dependent on the spreading attributes of smoke. Experimental results show that the proposed method can provide an early alarm at a lower false alarm rate before the fire burns up, and hence is very attractive for the important military, social security, commercial applications, and so on.

The smoke detection for early fire-alarming system base on video processing

The rapid spread in digital data usage in many real life applications have urged new and effective ways to ensure their security. Efficient secrecy can be achieved, at least in part, by implementing steganograhy techniques. Novel and versatile audio steganographic methods have been proposed. The goal of steganographic systems is to obtain secure and robust way to conceal high rate of secret data. We focus in this paper on digital audio steganography, which has emerged as a prominent source of data hiding across novel telecommunication technologies such as covered voice-over-IP, audio conferencing, etc. The multitude of steganographic criteria has led to a great diversity in these system design techniques. In this paper, we review current digital audio steganographic techniques and we evaluate their performance based on robustness, security and hiding capacity indicators. Another contribution of this paper is the provision of a robustness-based classification of steganographic models depending on their occurrence in the embedding process. A survey of major trends of audio steganography applications is also discussed in this paper.

https://link.springer.com/content/pdf/10.1186%2F1687-4722-2012-25.pdf

Comparative study of digital audio steganography techniques

Quantum technologies hold the promise of not only faster algorithmic processing of data, via quantum computation, but also of more secure communications, in the form of quantum cryptography. In recent years, a number of protocols have emerged which seek to marry these concepts for the purpose of securing computation rather than communication. These protocols address the task of securely delegating quantum computation to an untrusted device while maintaining the privacy, and in some instances the integrity, of the computation. We present a review of the progress to date in this emerging area.

/pdf/private-quantum-computation-an-introduction-to-blind-quantum-56is095nwo.pdf

Private quantum computation: an introduction to blind quantum computing and related protocols

The paper presents a new steganographic method for IP telephony called TranSteg (Transcoding Steganography). Typically, in steganographic communication it is advised for covert data to be compressed in order to limit its size. In TranSteg it is the overt data that is compressed to make space for the steganogram. The main innovation of TranSteg is to, for a chosen voice stream, find a codec that will result in a similar voice quality but smaller voice payload size than the originally selected. Then, the voice stream is transcoded. At this step the original voice payload size is intentionally unaltered and the change of the codec is not indicated. Instead, after placing the transcoded voice payload, the remaining free space is filled with hidden data. TranSteg proof of concept implementation was designed and developed. The obtained experimental results are enclosed in this paper. They prove that the proposed method is feasible and offers a high steganographic bandwidth while introducing small voice degradation. Moreover, TranSteg detection is difficult to perform when compared with existing VoIP steganography methods.

/pdf/using-transcoding-for-hidden-communication-in-ip-telephony-aha5n9cndu.pdf

Using transcoding for hidden communication in IP telephony

SURF (Speeded Up Robust Features) is one of the famous feature-detection algorithms. This paper proposes a panorama image stitching system which combines an image matching algorithm; modified SURF and an image blending algorithm; multi-band blending. The process is divided in the following steps: first, get feature descriptor of the image using modified SURF; secondly, find matching pairs, check the neighbors by K-NN (K-nearest neighbor), and remove the mismatch couples by RANSAC(Random Sample Consensus); then, adjust the images by bundle adjustment and estimate the accurate homography matrix; lastly, blend images by multi-band blending. Also, comparison of SIFT (Scale Invariant Feature Transform) and modified SURF are also shown as a base of selection of image matching algorithm. According to the experiments, the present system can make the stitching seam invisible and get a perfect panorama for large image data and it is faster than previous method.

SURF applied in panorama image stitching

This study presents a robust and semi-blind watermarking by embedding information into low frequency AC coefficients of Discrete Cosine Transform (DCT). Since the imperceptibility is the most significant issue in watermarking, the DC value is maintained unchanged. The proposed methods utilize the DC values of the neighboring blocks to predict the AC coefficients of the center block. The low frequency AC coefficients are modified to carry watermark information. The Least Mean Squares (LMS) is employed to yield the intermediate filters, cooperating with the neighboring DC coefficients to precisely predict the original AC coefficients. Two watermarking methods, namely Watermark Embedding in the Predicted AC Coefficient (WEPAC) and Watermark Embedding in the Original AC coefficient (WEOAC), are presented in this study. Moreover, many attacks are addressed to show the robustness of the proposed methods.

International Conference on Intelligent Information Hiding and Multimedia Signal Processing

This study presents a robust and semi-blind watermarking by embedding information into low frequency AC coefficients of discrete cosine transform (DCT). Since the imperceptibility is the most significant issue in watermarking, the DC value is maintained unchanged. The proposed methods utilize the DC values of the neighboring blocks to predict the AC coefficients of the center block. The low frequency AC coefficients are modified to carry watermark information. The least mean squares (LMS) is employed to yield the intermediate filters, cooperating with the neighboring DC coefficients to precisely predict the original AC coefficients. Two watermarking methods, namely watermark embedding in the predicted AC coefficient (WEPAC) and watermark embedding in the original AC coefficient (WEOAC), are presented in this study. Moreover, many attacks are addressed to show the robustness of the proposed methods.

Yu-Cheng Lu

Papers

International Conference on Intelligent Information Hiding and Multimedia Signal Processing

Variance-Classified Capacity Watermarking Using Discrete Cosine Transform