CoPreTHi is a Java based web application, which combines the results of methods that predict the location of transmembane segments in protein sequences into a joint prediction histogram. Clearly, the joint prediction algorithm, produces superior quality results than individual prediction schemes. The program is available at http://o2.db.uoa.gr /CoPreTHi

Mail sorting automation is yet a partially solved challenge. Due to no fixed positions of the semantic information in envelope images, part of this challenge is the automatic location of address blocks. In this paper we approach this problem by proposing a new postal envelope segmentation method based on 2-D histogram clustering and watershed transform. Segmentation task consists in detecting t...

Knowledge of what dose-volume histograms can be expected for a previously unseen patient could increase consistency and quality in radiotherapy treatment planning. We propose a machine learning method that uses previous treatment plans to predict such dose-volume histograms. The key to the approach is the framing of dose-volume histograms in a probabilistic setting.The training consists of esti...

In recent years, with the development of application research on medical images and medical documents, it is urgent to embed data, such as patient's personal information, diagnostic information and verification information into medical images. Reversible data hiding for medical images is the technique of embedding medical data into medical images. However, most existed schemes of reversible dat...

This proposed scheme reversibly embeds data into image predictionerrors by using histogram-pair method with the following four thresholds for optimal performance: embedding threshold, fluctuation threshold, leftand right-histogram shrinking thresholds. The embedding threshold is used to select only those prediction-errors, whose magnitude does not exceed this threshold, for possible reversible ...

Reversible image watermarking enables the embedding of copyright or useful information in a host image without any loss of information. Here a novel technique to improve the embedding capacity i.e. reversible watermarking using an adaptive prediction error expansion & pixel selection is proposed. This work is an improvement in conventional Prediction Error Expansion by adding two new techniques...

An algorithm for determination of the number of modes in a gray-level image histogram is presented in this paper. The hypothesis is that the image histogram’s pdf is approached by a mixture of Gaussians. Then, the algorithm tries to estimate the number of components in the mixture, which is an important parameter when using the maximum likelihood technique to estimate the remaining of parameter...

This paper presents a block-based ciphering scheme that employs the 2D discretized chaotic Standard map (CSM) in three different operation modes. The employed modes include electronic codebook (ECB), output feedback (OFB) and cipher block chaining (CBC) In presented CSM with OFB CBC, initiation vector (IV) is as primary secret key. CBC has two merits. first merit ability of ECB, to encipher ima...

Reversible data hiding has drawn a lot of interest recently. Being reversible, the original image can be completely restored without distortion. In this paper, a novel reversible data hiding scheme is proposed, which is based on histogram shifting of prediction errors. The JPEGLS prediction method is employed. We apply the peak point of a histogram in a prediction error (PE) image to generate a...

A large-capacity information hiding algorithm for HEVC is proposed. We modify the intra prediction modes in 4x4 luminance blocks to embed secret information. According to the probability distribution of the statistical optimal prediction mode and suboptimal prediction mode, we are establishing a mapping relationship between prediction modes and secret information. Modifying the intra prediction...