The increasing need for information security has led to more attention being given to biometrics-based, automated personal identification. Among existing biometric approaches, the human iris is the most promising technique. In general, an iris recognition algorithm includes four basic steps: image quality assessment, image preprocessing, image feature extraction, and image matching. This paper ...

Due to its distinctiveness, the human iris is a popular biometric feature used to identity a person with high accuracy. The “Grand Challenge” in iris recognition is to have an effective algorithm for subject verification or identification under a broad range of image and environmental conditions. This paper presents both baseline performance results and an enhanced version of VASIR (Video-based...

Image Classification is the evolution of separating or grouping an image into different parts. The good act of recognition algorithms based on the quality of classified image. The good feat of recognition algorithms based on the quality of classified image. An important problem in SAR image application is accurate classification. Image segmentation is the mainly practical loom among virtually a...

One of the major advantages of face recognition, compared to other biometrics, is the ease-of-use: no contact with the sensor, fast, in-line with the human way of recognizing people. In a border control scenario, fully automated gates using face recognition have now been deployed. As a passenger may use an automated solution only once in his life, the deployed system must operate with as little...

with an increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention. iris recognition, as an emerging biometric recognition approach, is becoming a very active topic in both research and practical applications. in general, a typical iris recognition system includes iris imaging, iris liveness detection, and recognition. this rese...

X-ray CT images have been widely used in clinical diagnosis in recent years. A modern CT scanner can generate about 1000 CT slices to show the details of all the human organs within 30 seconds. However, CT image interpretations (viewing 500-1000 slices of CT images manually in front of a screen or films for each patient) require a lot of time and energy. Therefore, computer–aided diagnosis (CAD...

Fundamental part of a numismatist’s work is the classifi cation of coins according to standard reference books. For this application, image processing techniques like Image Enhancement, Image Segmentation and Optical Character Recognition (OCR) are investigated. The recently started European project COINS combines these two research areas by developing a vision based system for automated coin r...

Recently, a flexible image database retrieval system where iniage keywords call be captured automatically is strongly ~equired, to manage a practical Iium1)er of image data sl~ccessfully. But image recognit io~i /~~nderstar i t l i~ig technology level is not generally inefficient enough to achieve this requirement. I11 order to overcome this problem, we propose a new i~iiag(, data1)ase framewor...

Porosity is a common phenomenon in fabricated parts, which cause stress concentration and leads to yielding, brittle fraction fatigue of structures makes porosity recognition analyzing very important increase efficiency decrease the defects manufactured parts. Many researches have been done order detecting recognizing pores material by different numerical experimental methods. In this paper, an...