Abstract-Sign language continues to be the preferred method of communication among the deaf and the hearing-impaired. Advances in information technology have prompted the development of systems that can facilitate automatic translation between sign language and spoken language. More recently, systems translating between Arabic sign and spoken language have become popular. This paper reviews systems and methods for the automatic recognition of Arabic sign language. Additionally, this paper highlights the main challenges characterizing Arabic sign language as well as potential future research directions.Index Terms-Arabic sign language recognition (ArSLR), continuous sign recognition, image-based, isolated word recognition, sensor-based.

This paper represents a new and intelligent system for license plate recognition used in many cases, for example: unattended parking lots, security control of restricted areas, traffic law enforcement, congestion pricing, and automatic toll collection. The proposed system is a process based on a combination of the complement methods that increases the accuracy of output data and is generally accountable on the images that have many problems and aren't answerable with a particular approach. The performance of this system is in a form that, firstly, the input image is given to all the complement methods in order for the location of the plate candidate to be determined, then their response is investigated according to the valence function and finally the location of plate is properly determined by the majority of votes and ensures the accuracy of output data. If the complement methods are chosen correctly, this proposed system will be responsive to the images in which the license plate recognition is likely. This method has been tested on two data sets that have different images of the background, considering the distance, and angle of view so that the correct extraction rate of plate location reached at 100% and 99% respectively.