A Method of Steganography – P Message With Q Coefficient (SPMQC)

In this paper, we are going to propose a method for Steganography- which is based on deceiving χ2 algorithm. Since the cover image coefficients and stego image coefficients histograms have significant differences for purposes of statistical properties, statistical analysis of χ2-test reveals the existence of hidden messages inside stego image. We are introducing an idea for hiding messages in the cover image. It causes that DCT (Discrete Cosine Transforms) coefficient histogram not to have remarkable modification before and after embedding message. As a result, identifying the hidden message inside an image is impossible for an eavesdropper through χ2 -test. In this paper, we are proposing a better method with developing this algorithm. In fact, the capacity and the security of embedding messages increase extremely.DOI:http://dx.doi.org/10.11591/ijece.v3i2.201

A soft computing approach for the memory storage of a sound signal processor

This paper tries to create a new biologically inspired abstract model for the sound signal processing.The abstract model also shows the memory storage for the sound signal processor.This research adapts the functions from the biologically-inspired entities, which are the human auditory system and the human brain.This research aims to provide integrated and structured database to store the sound signal processing data.This research provides the framework to the implementation of the soft computing approach for the memory storage of a sound signal processor. This paper is a preliminary investigation paper. Therefore, this research creates the abstract model for the Biologically-Inspired Sound Signal Analyzer (BISSA) as a new idea for information gathering

A new abstraction model for biologically-inspired sound signal analyzer

This paper studied the human ear and human brain as a new idea to analyze sound. The human ear to be exact; the eardrum detects the sound signal and the cochlea filters the frequency signal. Subsequently, the brain is capable to recognize and learn the sound signal. This research mapped the biologically-inspired ability to computational process then developed an abstraction model. From this model it provided a guideline to obtain the capability requirements for the of sound signal analyzer as a new idea for information retrieval. The research aims to generate faster and more detailed results as well as to achieve better accuracy in producing definite sound. Therefore, this research proposed an abstraction model of human ear and human brain to developed biologically-inspired sound signal analyzer (BISSA

Impulsive noise suppression from images with the noise exclusive filter

A novel impulsive noise elimination filter, entitled noise exclusive filter (NEF), which shows a high performance at the restoration of images distorted by impulsive noise, is proposed in this paper. NEF uses chi-square goodness-of-fit test in order to detect the corrupted pixels more accurately. Simulation results show that the proposed filter achieves a superior performance compared with the other filters mentioned in this paper in terms of noise suppression and detail preservation, particularly when the noise density is very high. The proposed method also achieves the robustness and detail preservation perfectly for a wide range of impulsive noise density. NEF provides efficient filtering performance with reduced computational complexity

Impulsive Noise Suppression from Images with the Noise Exclusive Filter

A novel impulsive noise elimination filter, entitled noise exclusive filter (NEF), which shows a high performance at the restoration of images distorted by impulsive noise, is proposed in this paper. NEF uses chi-square goodness-of-fit test in order to detect the corrupted pixels more accurately. Simulation results show that the proposed filter achieves a superior performance compared with the other filters mentioned in this paper in terms of noise suppression and detail preservation, particularly when the noise density is very high. The proposed method also achieves the robustness and detail preservation perfectly for a wide range of impulsive noise density. NEF provides efficient filtering performance with reduced computational complexity.</p