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Register a new userIdentify people through an off-angle iris image using the eigenvalues
التعرف على الأشخاص من خلال صورة مع زاوية لقزحية العين (Off-Angle Iris) باستخدام القيم الذاتية
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يقدم هذا البحث تقنية جديدة لاستخلاص الميزات من قزحية العين ضمن نظام التعرف على الأشخاص باستخدام صورة قزحية العين المأخوذة في بيئات غير مثالية، و بالتحديد الصور المأخوذة بكاميرا تصنع زاوية مع القزحية، أو إصطلاحاً (off-angle iris) و هي الحالة الشائعة لصور القزحية.
This paper presents a new technique to extract the features of a common case of images of the iris called off-angle iris which taken for persons identification system. The main problem when using biological iris measurements to identify the persons is the difficulty of identifying and extracting features of the iris. This problem increasing when dealing with off-angle iris and it leading to decrease system accuracy and increase system rate error.
References used
Mcdonald J, 2008- Hand Book of Biological Statistic. Sparky House Publishing Baltimore, Maryland, 291p
Bass M, Decusatis C, Enoch J, Lakshminarayanan V, 2009- Handbook of Optics, Volume I: Geometrical and Physical Optics, Polarized Light, Components and Instruments. McGraw-Hill Professional, 3rd Ed, 1248p
Abhyankar A, Hornak L, Schuckers S, 2010 Pattern Recognition A novel biorthogonal wavelet network system for off-angle iris recognition, Vol. 43, Issue 3, pp. 987–1007
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The study suggests designing a weighting model for iris features and selection of the
best ones to show the effect of weighting and selection process on system performance.
The search introduces a new weighting and fusion algorithm depends on the i
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class differences and the fuzzy logic. The output of the algorithm is the feature’s weight of
the selected features. The designed system consists of four stages which are iris
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implementation and recognition. System suggests using region descriptors for defining the
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coordinates via rotation and selection of radius-size pixels of fixed window from center to
circumference. Feature extraction stage is done by wavelet vertical details and the
statistical metrics of 1st and 2nd derivative of normalized iris image. At weighting and
fusion step the best features are selected and fused for classification stage which is done by
distance classifier. The algorithm is applied on CASIA database which consists of iris
images related to 250 persons. It achieved 100% segmentation precision and 98.7%
recognition rate. The results show that segmentation algorithm is robust against
illumination and rotation variations and occlusion by eye lash and lid, and the
weighting_selection_fusion algorithm enhances the system performance.
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the alarm in case of the existence of the picture of a student who does not belong to the
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The robotic manipulator's control process involves many
engineering challenges from mechanical design phase to the phase
of programming. The inverse kinematics problem is one of the most
difficult challenges, as it requires determining the angles
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for a desired position of the end-effector, the difficulty of this
problem comes from the none linearity and the possibility of
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solutions were proposed to solve the issue of inverse kinematics;
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