Enhancement Segmentation Technique for Iris Recognition System Based on Daugman’s Integro-Differential Operator Asama Kuder Nsaef Institute of Visual Informatics (IVI) Universiti Kebangsaan Malaysia Bangi‚ Selangor‚ Malaysia osama_ftsm@yahoo.com Azizah Jaafar Institute of Visual Informatics (IVI) Universiti Kebangsaan Malaysia Bangi‚ Selangor‚ Malaysia aj@ftsm.ukm.my Khider Nassif Jassim Faculty of Management and Economics Department of Statistics University of Wasit Al-Kut‚ Iraq khider_st@yahoo
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Mini Project Report on Iris Recognition By Medini Brahma : Roll 071310 No. 31320016 Saurav Kant Kumar : Roll 071310 No. 31320013 Sourav Chakravarty : Roll 071310 No. 31320014 Under the supervision of Mr. Abhijit Biswas (Assistant Professor) Department of Information Technology Department of Information Technology ASSAM UNIVERSITY SILCHAR‚ DORGACONA-788011 1 DECLARATION We hereby declare that the work on the project entitled “Iris Recognition” under the guidance of
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IRIS DATA ANALYSIS USING BACK PROPAGATION NEURAL NETWORKS Sean Van Osselaer Murdoch University‚ Western Australia ABSTRACT This project paper refers to experiments towards the classification of Iris plants with back propagation neural networks (BPNN). The problem concerns the identification of Iris plant species on the basis of plant attribute measurements. The paper outlines background information concerning the problem‚ making reference to statistics and value constraints identified
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Fingerprint based Attendance System This sensor unit captures finger’s print image and then converts it into the alike template and saves them into its memory as per selected ID . All the procedure is like taking an image of finger’s print‚ switch it into templates and storing as ID etc. at whatever time user place his finger over fingerprint module then fingerprint module captures finger image‚ and look for if any ID is associated with this fingerprint in the system. If fingerprint ID is identified
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Disadvantages: a. Iris Recognition is intrusive. b. Due to fluctuations‚ the Iris is hard t pinpoint c. Iris Recognition is very expensive A. The iris is a small target and a scan cannot be performed properly if the person is more than a few meters way. In order for an iris to be properly scanned‚ the person’s head must be completely still. Eyelashes‚ lenses‚ and anything that would cause a reflection‚ could all make a scan difficult. It is a moving target and can be obscured by objects such as
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IRIS Goddess of the Rainbow: In Greek mythology‚ Iris is the personified goddess of the rainbow. She is regarded as the messenger of the gods to humankind‚ and particularly of the goddess Hera whose orders she brought to humans. She is able to change shapes and when delivering messages to mortals Iris assumes the appearance of a mortal known to those who receive the message. Iris is the daughter of the Titan Thaumas and the nymph Electra. Thaumas (his name means "wonder") is a Greek sea god
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Project of Mythological Characters: IRIS Iris is a goddess of sea and sky‚ whose work is as the messenger of the gods and her representation is the rainbow. She takes the messages from the gods‚ especially from Hera and Zeus‚ to the Earth and to the deep ocean and the underworld. So she connects the mortal world to the god`s and immortal’s world. She is always carrying a caduceus‚ that is like a scepter or a magic wand which it`s related with Apollo; who gave it to Iris to link or connect the mortal
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Breathe. You have to breathe‚ Iris. You have to snap out of this‚ it’s not real. None of this is real. “Ms. Montez‚ you have to open your eyes‚ dear. You have to be coherent to continue with your session‚” the man said. I hate him‚ I hate this stupid man. He has no idea what he’s talking about. It’s all lies‚ what he’s telling me. Nothing is true. “Ms. Montez!” he shouts. My eyes shoot open‚ startled at the doctor’s harsh tone. My chest is rising and falling rapidly‚ my body trickling with perspiration
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Paul Perez ID: 2247878 November 9th‚ 2010 Project Two Analysis The “Iris” data set contains 3 classes‚ Iris Setosa‚ Iris Versicolour‚ and Iris Virginica‚ each with 50 attributes. Each attribute contains the Iris’ sepal and petal length‚ as well as its sepal and petal width in centimeters for its class. The “Adult” data set contains 48‚842 records‚ each with 15 variables to analyze. Those fields include age‚ work class‚ education‚ education-num‚ marital-status‚ occupation‚
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INFORMATION SYSTEM AND FINANCIAL ANALYSIS FOR STARBUCKS MODULE: FINANCIAL ANALYSIS AND MANAGEMENT SECTION 1: Introduction: The need of management Management is the key to success for a good business. These days management became universal‚ no matter what country the organisation is located in. The need of management is vital in all types and sizes of organisations. Managers in all types of organisations will plan‚ organise‚ lead‚ control and take strategic decisions. To make
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