This paper presents an intelligent translation system for the signs of some words and letters in the Arabic sign language. The proposed translation system does not depend on any visual markings or gloves used to complete the recognition process. The proposed translation system deals with images, which allows the user to interact with the system in a natural way. The proposed translation system consists of four main phases; Preprocessing images phase, feature extraction phase, matching strategy phase, and Display Text Translation phase. The extracted features used are combining intensity histogram features and Gray Level Co-occurrence Matrix (GLCM) features, Experiments revealed that the proposed system was able to recognize the 19 Arabic alphabets and word with an accuracy of 73%.

This study presents a novel framework to help people with color impairment in identifying colors. The proposed framework consists of three stages. These stages are electronically performing the Ishihara test, performing the color blindness type recognition test, and guiding the person to color by voice. The first stage, the person is subjected to an electronic color blindness test, by displaying different plates containing several points of different sizes and colors. The person is required to correctly identify the number or shape in the plate and at the end, the system determines the extent to which a person is color blind. The second stage is a color recognition test to determine the type of color blindness. If there is difficulty in determining red, this is called protanopia. But the difficulty in identifying the green color is called deuteranopia. While the inability to recognize the blue color is called tritanopia. And finally, the difficulty in identifying the colored style is called achromatopsia. The third stage is assistance phase and is divided into three subsectors are: smart educational system, identifying colors and extracting the content. The proposed system differs from other systems in that it is an integrated system. It includes identifying color blindness, determining its type, and finally aiding color blindness person. Also, it is the first system that deals with the rare type of color blindness called achromatopsia in addition to its other three types. The results obtained confirmed that the proposed system as well as the smart educational system are characterized by high accuracy and effectiveness.