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People involved: - Li Fang (Lecturer) - Maylor Karhang Leung (Assoc Prof) - Kean Fatt Choon (Final Year Project student) Palmprint Classification

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Task Create a hierarchical system to improve the speed of palmprint recognition

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Contents Victor - Victor - Introduction, Research, conventional process Tejas - Tejas - Algorithm, explanation of various categories

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Introduction What is palmprint recognition? Form of computer-aided personal recognition Capturing images of palmprint and matching it with the database Use for security purposes in many countries

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Definitions Introduction to principal lines Life Line Head Line Heart Line

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Rationale Why palmprint? Widely used by many security agencies. Cost effective Non-intrusive Possible to build highly accurate biometric system

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Rationale Why others methods such as iris and fingerprint are not highly effective Why others methods such as iris and fingerprint are not highly effective ? Iris input devices are expensive. Iris is intrusive Fingerprint require high definition capturing devices. Some may be finger deficient

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Contains 1000 images Palmprint Capture Input Database Result Output BEGIN Match with users registered palm print in the database? END False True

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Limitations Image captured has to be matched with every single image in database Time consuming Too high computational complexity to be applicable

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Aims & Expectations Our aim is to speed up this process by adding in 2 extra filters before the palm print is matched We expect to increase the speed of the recognition which is one of the most deterring limitation

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Survey Conducted a survey among people living in Singapore Gender Age Nationality Survey can be used in our study and design of algorithm which will suit the residents here.

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Survey Result From our survey, The population palms can be classified into 6 categories (elaborated in the later slide) Majority of the population lies in one category. However, significant amount of the population still falls under the other categories

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Studies have shown... According to the algorithm proposed on the research paper According to the algorithm proposed on the research paper The algorithm proposed categorizes the palmprints into 6 categories Palm Categories

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Cat 1 Cat 5Cat 4 Cat 3 Cat 2 Cat 6 Palm Categories

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Result Algorithm proposed by the research paper

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Category 5

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New Algorithm Why a new algorithm is required? 78% of the people lie in the 5th category Based on the current system, the input image has to be matched with every image in the database before the result is obtained

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Flowchart Image matching with the images in same category in data base Categories with the new algorithm Result Categories with the initial algorithm Belong to Category 5? N Input Palmprint Y Image matching with the images in same category in data base Categories with the new algorithm Result Categories with the initial algorithm Belong to Category 5? N Input Palmprint Y

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Flowchart Image matching with the images in same category in data base Categories with the new algorithm Result Categories with the initial algorithm Belong to Category 5? N Input Palmprint Y

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Flowchart In Cat. 1 Image matching with the images in same category in data base Categories with the new algorithm Result Categories with the initial algorithm Belong to Category 5? N Input Palmprint Y

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Flowchart In Cat. 1 NOT CAT. 5 Image matching with the images in same category in data base Categories with the new algorithm Result Categories with the initial algorithm Belong to Category 5? N Input Palmprint Y

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Flowchart Image matching with the images in same category in data base Categories with the new algorithm Result Categories with the initial algorithm Belong to Category 5? N Input Palmprint Y In Cat. 1 NOT CAT. 5 Not Cat 5 Compare Result

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Flowchart Image matching with the images in same category in data base Categories with the new algorithm Result Categories with the initial algorithm Belong to Category 5? N Input Palmprint Y

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Flowchart Image matching with the images in same category in data base Categories with the new algorithm Result Categories with the initial algorithm Belong to Category 5? N Input Palmprint Y In Cat. 5

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Flowchart Image matching with the images in same category in data base Categories with the new algorithm Result Categories with the initial algorithm Belong to Category 5? N Input Palmprint Y In Cat. 5 True

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Flowchart Image matching with the images in same category in data base Categories with the new algorithm Result Categories with the initial algorithm Belong to Category 5? N Input Palmprint Y In Cat. 5 E.g cat. A

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Flowchart Image matching with the images in same category in data base Categories with the new algorithm Result Categories with the initial algorithm Belong to Category 5? N Input Palmprint Y In Cat. 5 Cat A. Compare Cat A Result

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New Process Contains 1000 Images Palmprint Capture Input Database Result Cat A Cat BCat C Cat D Cat E Not Cat 5

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New Algorithm Step 1 The first line connected from the end of the little finger to the intersection of the life line and head line (green line) The second line is connected from the end of life line to intersection of life and head line (red line) The third line is connected from point of intersection green line and heart line to midpoint of red line (purple line)

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New Algorithm Step 2 Draw a triangle inside the triangle by connecting the mid points of the each line Divide the two triangle into 4 parts as shown

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New Algorithm Step 3 Draw a line from end of heart line to end of life line Draw a line from beginning of heart line to the intersection of life line and head line The location of the point of intersection of these 2 lines can then be used to categorize the palm

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Implementation Category A Category B Category C Category D Category E

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Result We tried this algorithm on 100 subjects The pie chart above shows the percentage of each category It can be concluded that algorithm proposed is effective

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Summary Our research showed that process of palmprint recognition is inefficient and can be improved Our research showed that process of palmprint recognition is inefficient and can be improved Our survey analysis revealed that most people lie in one particular category Our survey analysis revealed that most people lie in one particular category Proposed a robust algorithm via study of characteristics of principal lines to reinforce the method of palmprint classification Proposed a robust algorithm via study of characteristics of principal lines to reinforce the method of palmprint classification Tried out the proposed algorithm on 100 subjects to investigate its effectiveness Tried out the proposed algorithm on 100 subjects to investigate its effectiveness

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The End

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