Individual’s eye recognition is an important issue in applications such as security systems, credit card control and guilty identification. Using video images cause to destroy the limitation of fixed images and to be able to receive users’ image under any condition as well as doing the eye recognition. There are some challenges in these systems; changes of individual gestures, changes of light, face coverage, low quality of video images and changes of personal characteristics in each frame. There is a need for two phases in order to do the eye recognition using images; revelation and eye recognition which will use in the security systems to identify the persons. The main aim of this paper is innovation in eye recognition phase. In this paper, a new and fast method is proposed for human eye recognition that can quickly specify the human eye location in an input image. In the proposed method, eyes will be specified in an input image with a CNN neural network. This proposed method is tested on different images and provided highest accuracy for the image recognition which used in security systems.

<span>One of the significant techniques for hiding important information (such as text, image, and audio) is steganography. Steganography is used to keep this information as secret as possible, especially the sensitive ones after the massive expansion of data transmission through the Internet inside a conventional, non-secret, file, or message. This paper uses the American standard code for information interchange (ASCII) mapping technique (AMT) to hide the data in the color and grey image by converting it in a binary form, also convert the three levels of the red, green, and blue (RGB) image and grey image in the binary form, and then hide the data through hiding every two bits of the text in the two bits of one of the levels from the RGB image and grey image that means the text will be distributed throughout the images and allows hiding large amounts of data. That will send the information in a good securing way.</span>