Facial feature extraction / Muhammad Marzuq Mohd Sharip

By: Material type: TextTextPublication details: Kuantan, Pahang : UMP, 2009Description: xiv, 50 p. : ill. (some col.) ; 30 cm. + 1 computer discISBN:
  • THE0008085(Local)
Other title:
  • Facial feature extraction [computer file]
Subject(s): Dissertation note: Project paper (Bachelor of Electrical Engineering (Control and Instrumentation)) -- Universiti Malaysia Pahang - 2009 Abstract: This project presents the facial feature extraction system and face recognition system. The test image that used for this project contain various type. There are ten different images of each of 40 disntinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions; open or closed eyes, smiling or not smiling, and facial details; glasses or no glasses. All the images were taken against a dark homogeneous background with the subjects in an upright, frontal position with tolerance for some side movement. For the facial feature extraction system, it is more focus on eye extraction. The eye will extracted from the face by finding the centroid of the eye region using threshold technique. For the recognition system, Principle Component Analysis (PCA) is used to match the test image with the database image. The system will find which database image has a maximum percentage based on similarity of the pattern of the image
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Item type Current library Call number Copy number Status Date due Barcode
Final Year Report Final Year Report UMPLIB PEKAN TK7882.B56 F33 2009 rs Bc. (Browse shelf(Opens below)) 1 Not for loan 0000058220
Final Year Report Final Year Report UMPLIB PEKAN CD 5310 | TK7882.B56 F33 2009 rs Bc. (Browse shelf(Opens below)) 1 Not for loan 0000058221

Project paper (Bachelor of Electrical Engineering (Control and Instrumentation)) -- Universiti Malaysia Pahang - 2009

Bibliography : p.[40]- 46

This project presents the facial feature extraction system and face recognition system. The test image that used for this project contain various type. There are ten different images of each of 40 disntinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions; open or closed eyes, smiling or not smiling, and facial details; glasses or no glasses. All the images were taken against a dark homogeneous background with the subjects in an upright, frontal position with tolerance for some side movement. For the facial feature extraction system, it is more focus on eye extraction. The eye will extracted from the face by finding the centroid of the eye region using threshold technique. For the recognition system, Principle Component Analysis (PCA) is used to match the test image with the database image. The system will find which database image has a maximum percentage based on similarity of the pattern of the image

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