Majdi Salameh, IT Department, King Abdul Azziz University.
Abstract— Arabic Digits recognition has the lights spotted on lately, since it could be useful in a wild range of fields. This paper provides an easy and fast technique to recognizing Arabic digits. This paper presents two methods about enhancing recognition rate for typewritten Arabic digits (Hindi). First, is node method that calculates number of ends of the given shape and conjunction nodes as well, the second method is fuzzy logic for pattern recognition that studies each shape from the shape, and then classifies it into the numbers categories. Two stages are going to be done by the two given methods, to recognize the Arabic digit, each come out with its own result and afterward compounds these result to obtain the final solution and statistical analysis. Several steps are taken in the recognition system, starting with the image processing, then feature extraction and the last step is classification. The image processing includes converting into binary, cropping the digit in single image, and getting a skeleton of the shape by thinning it. Feature extraction includes number of terminal and conjunction nodes from nodes method and two characters to specify the curve lines group for shapes and third number to know the position of end nodes according to conjunction nodes in similar digit such as 7 , 8 . The recognition includes compound between two vectors, one from each method. The proposed technique was implemented and tested the experimental results give high recognition rate for some fonts and either less for other fonts because of due to irregularity of some fonts (Andalus) or failing for one of the methods. The dataset contains multi-size for the digits from 0 to 90.
Keywords-Arabic digit recognition; Arabic number recognition; node method; statistical analysis; multi size numeral recognition.
Rashiq R. Marie, Computer Science Department, Faculty of Science and Information Technology, Zarka University, Zarka, Jordan.
Abstract— The two common different techniques for securing data transmission are cryptography and steganography. Steganography is not intended to replace cryptography but rather to supplement it. If a message is encrypted and hidden with a steganographic method it provides an additional layer of protection and reduces the chance of the hidden message being detected. In
this paper, two layers of security are used to secure the hidden information and to add more complexity for steganalysis. We combined schemes of cryptography with steganography in one system called CryptSteg for hiding secret messages. By CryptSteg we first encoded the secret message (plain-text) using chaotic stream cipher based on a secret key (crypto-key) then the encoded data was hidden behind a cover-image by changing Kth least significant bits (k-LSB) of cover-image pixels in random way which makes it superior to the conventional approach. A random-like sequence generated by a chaotic map is used as the reference for embedded positions. The randomness of the position of pixels on which the encrypted message to be embedded is decided by the stego- key. The two keys are shared between the sender and the receiver and they are encrypted and transmitted to the other party in a secured form. Experimental results show that the proposed CryptSteg system achieve a much higher visual quality as indicated by the high PSNR values of hiding secrete message bits in the image thus reduces the chance of the confidential message being detected and enables secret communication.. Moreover, using unauthorized keys (Crypto-key, Stego-Key) gets messages totally different from the original ones even the error keys are very close to the authorized one.
Keywords- Chaotic Stream; MSB; Stego-Key; Crypto-Key; LSB; Cover-image; Stego-Image.