Abstract

Abstract
Assistive technology enables people to achieve independence in the accomplishment of their daily tasks and enhance their quality of life. Navigation systems to assist visually impaired people that use computer vision techniques are very resource intensive and as such, not suitable for mobile devices. This work describes a computer vision algorithm intended to reduce processing demands with possible application in portable devices. The model proposed employs 2D-Ensemble Empirical Mode Decomposition (2D-EEMD) in order to reduce the problem complexity. It uses a combination of Peano-Hilbert space filling curves as a dimension reduction of image data and EEMD to implement a fast algorithm. Tests results have shown that Peano-Hilbert EEMD exhibits substantially reduced processing power compared with 2D-EEMD approaches, enabling new opportunities for its use in portable applications on low computer power devices.

Abstract
According to the World Health Organization in 2002 more than 161 million people were visually impaired [1]. The mobility of the visually impaired reveals itself to be a rather complex task, even with the support of inclusive technologies. Currently, the most widespread and used means by the visually impaired people are the white stick and the guide dog, however both show some difficulties in their mobility. The white stick only detects obstacles at the ground level, whilst obtaining a guide dog correctly trained in Portugal is an expensive and slow solution [2], given that the communication between the visually impaired person and the dog is limited. If the blind person had access to reliable information, and in real time, about the environment in which he lives, it certainly would be safer for him to move around it [3]. Thus, more and more, with the increasing development of the technologies, there is the possibility of creating systems that assist the visually impaired people in their task of detecting the obstacles and subsequent orientation. The objective of this article is to create a system that allows the capture of images in real time and that accomplishes the segmentation resorting to the information with disparity. Later on, the result of the image segmentation will be used in a system that offers the visually impaired person information on the environment that surrounds him. The image acquisition is done through a system of stereo vision that captures images from the surrounding environment as the user moves around.

Abstract
Vehicle number plate recognition systems are expected to have numerous applications in traffic surveying and monitoring, e,g. finding stolen cars and controlling access to car parks. In this paper algorithmic improvements to a previous version of a number plate reading system are described. The work builds on the experience gained by the Computer Vision Group at the University of Bristol. This paper addresses the problem of locating the number plate area in the image and proposes a new line based method for number plate location, which is suitable for realtime number plate recognition.

Abstract

Abstract