A system to communicate hidden information using color images

The objective of this paper is to present a system to communicate hidden information among different users by means of images. The tasks that the system is able to carry on can be divided in two different groups of utilities, implemented in java. The first group of utilities are related with the possibility to hide information in color images, using a steganographic function based on the least significant bit (LSB) methods. The second group of utilities allows us to communicate with other users with the aim to send or receive images, where some information have been previously embedded. Thus, this is the most significant characteristic of the implementation, we have built an environment where we join the email capabilities to send and receive text and images as attached files, with the main objective of hiding information.

An exercises editor for an e-learning environment

One of the most important tenets of e-learning is that it bridges work and learning. A great e-learning experience brings learning into the work environment. This is a key point, the capacity to construct a work environment when the student can develop proper tasks to complete the learning process. This paper describes a work environment based on the development of two tools, an exercises editor and an exercises viewer. Both tools are able to manage color images where, because of the implementation of basic steganographic techniques, it is possible to add information, exercises, questions, and so on. The exercises editor allows to decide which information must be visible or remain hidden to the user, when the image is loaded in the exercises viewer. Therefore, it is possible to hide the solutions of the proposed tasks; this is very useful to complete a self-evaluation learning process. These tools constitute a learning architecture with the final objective that learners can apply and practice new concepts or skills.

A Model to Visualize Information in a Complex Streets’ Network

his paper discusses a process to graphically view and analyze information obtained from a network of urban streets, using an algorithm that establishes a ranking of importance of the nodes of the network itself. The basis of this process is to quantify the network information obtained by assigning numerical values to each node, representing numerically the information. These values are used to construct a data matrix that allows us to apply a classification algorithm of nodes in a network in order of importance. From this numerical ranking of the nodes, the process finish with the graphical visualization of the network. An example is shown to illustrate the whole process.

Geometric 3D point cloud compression

The use of 3D data in mobile robotics applications provides valuable information about the robot’s environment but usually the huge amount of 3D information is unmanageable by the robot storage and computing capabilities. A data compression is necessary to store and manage this information but preserving as much information as possible. In this paper, we propose a 3D lossy compression system based on plane extraction which represent the points of each scene plane as a Delaunay triangulation and a set of points/area information. The compression system can be customized to achieve different data compression or accuracy ratios. It also supports a color segmentation stage to preserve original scene color information and provides a realistic scene reconstruction. The design of the method provides a fast scene reconstruction useful for further visualization or processing tasks.