Browsing Researchers by Subject "Face recognition"

Now showing items 1-17 of 17

    • Automated face localization and facial features detection using geometric information 

      Chai, Tong Yuen; Mohd Rizon, Mohamed Juhari, Prof. Dr.; Karthigayan, M.; Sugisaka, M.; Hazry, Desa, Dr.; Ibrahim, Z. (Malaysia-Japan University Center (MJUC), 2007-11-12)
      This paper presents algorithms to detect irises of both eyes and mouth from color and intensity images and extracts intensity valleys from the race region. Next, the algorithm extracts iris candidates from the valleys and ...

    • Automatic detection of face and facial features 

      Chai, Tong Yuen; Mohd Rizon, Mohamed Juhari, Prof. Dr.; Woo, San San; Sugisaka, M. (World Scientific and Engineering Academy and Society (WSEAS), 2008-02-20)
      An algorithm to automatically detect facial features from color images has been developed. First, face region is located using skin-color information. Then, the iris candidates are extracted from the intensity valleys ...

    • Biometric Identification: Face Recognition based on Iris Detection 

      Mohd Rizon, Mohd Juhari, Prof. Madya Dr.; R. Badlishah, Ahmad, Prof. Madya Dr.; Ahmad Nasir, Che Rosli (International Exhibition of Inventions, 2006-04-05)
      A new face recognition system using iris detection. Can be applied to a face image in which the position, scale and image- plan rotation are unknown.

    • The effects of compiler optimizations in face recognition system 

      Shuhaizar, Daud; Khalib, Z.I.K; R. Badlishah, Ahmad; Mohamad Rizon, Mohamed Juhari (Institute of Electrical and Electronics Engineering (IEEE), 2008)
      One of the few challenges facing face recognition systems is real time processing. In order for a face recognition system to be viable for real world implementations, it needs to be fast enough to track and identify facial ...

    • A face recognition system using template matching and neural network classifier 

      Muhammad Firdaus, Hashim; Puteh, Saad; Mohamed Rizon, Mohamed Juhari; Shahrul Nizam, Yaakob (Kolej Universiti Kejuruteraan Utara Malaysia, 2005-05-14)
      We develop a technique to identify an unknown person in a face image by using template matching and neural network classifier. The technique is separated into three main steps namely; preprocessing, feature extraction and ...

    • Face recognition using neural network 

      Azlan Zainul (Universiti Malaysia PerlisSchool of Mechatronic Engineering, 2008-03)
      This dissertation provides a study of camera-based face recognition research. There are two underlying motivations to conduct this project: the first is to study and analyze type of feature extraction method, and the second ...

    • Facial features for template matching based face recognition 

      Chai, Tong Yuen; Mohd Rizon, Mohamed Juhari, Prof. Dr.; Woo, San San; Tan, Ching Seong, Dr. (Science Publications, 2009)
      Problem statement: Template matching had been a conventional method for object detection especially facial features detection at the early stage of face recognition research. The appearance of moustache and beard had ...

    • Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion 

      Muthukaruppan, Karthigayan; Mohd Rizon, Mohamed Juhari; Sazali, Yaacob; Ramachandran, Nagarajan; Masanori, Sugisaka; Mohd Rozailan, Mamat (Institute of Electrical and Electronics Engineering (IEEE), 2007-10)
      In this paper, lip and eye features are applied to classify the human emotion using a set of irregular and regular ellipse fitting equations using genetic algorithm (GA). A South East Asian face is considered in this study. ...

    • Human faces: a review from detection to recognition 

      Mohamed Rizon, Mohamed Juhari; Muthukaruppan, Karthigayan; Sazali, Yaacob; Ramachandran, Nagarajan; Puteh, Saad; P. L. EhKan (Kolej Universiti Kejuruteraan Utara Malaysia, 2005-05-14)
      In this paper, we review researches on human faces from aspect of face recognition and face detection. Face emotion recognition are also reviewed. The study of human faces has much assistance on computer vision and machine ...

    • Investigation of facial artifacts on face biometrics using eigenface based single and multiple neural networks 

      Sundaraj, Kenneth (World Scientific and Engineering Academy and Society (WSEAS) Press, 2009)
      Biometrics has been an important issue pertaining to security in the last few decades. Departments or agencies entrusted with national security are increasingly installing surveillance cameras in strategic or critical areas ...

    • Japanese face emotions classification using lip features 

      Mohamad Rizon, Mohamed Juhari; Muthukaruppan, Karthigayan; Sazali, Yaacob; Nagarajan, R. (Institute of Electrical and Electronics Engineering (IEEE), 2007)
      In this paper, lip features are applied to classify the human emotion using a set of irregular ellipse fitting equations using Genetic algorithm. As Japanese, is considered in this study. All six universally accepted ...

    • Lifting scheme for human emotion recognition using EEG 

      Murugappan, M., Dr.; Mohd Rizon, Mohamed Juhari; Nagarajan, Ramachandran, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Ibrahim, Zunaidi; Hazry, Desa, Assoc. Prof. Dr. (IEEE Conference Publications, 2008-08)
      In recent years, the need and importance of automatically recognizing emotions from EEG signals has grown with increasing role of brain computer interface applications. The detection of fine grained changes in functional ...

    • A new approach for Face Recognition based on Iris 

      Mohamed Rizon, Mohamed Juhari (Kolej Universiti Kejuruteraan Utara Malaysia, 2004)
      I propose a system to identify the unknown person in a face image for which the position, scale and image-plane rotation of the face are unknown. The proposed system detects the iris of both eyes and normalizes the position, ...

    • Personalized face emotion classification using optimized data of three features 

      Muthukaruppan, Karthigayan; Ramachandran, Nagarajan; Mohd Rizon, Mohamed Juhari; Sazali, Yaacob (Institute of Electrical and Electronics Engineering (IEEE), 2007)
      In this paper, lip and eye features are applied to classify the human emotion through a set of irregular and regular ellipse fitting equations using Genetic algorithm (GA). South East Asian face is considered in this study. ...

    • Real-time detection of face and iris 

      Chai, Tong Yuen; Mohamed Rizon, Mohamed Juhari, Prof. Dr.; Muhammad Shazri (World Scientific and Engineering Academy and Society (WSEAS), 2009-06)
      In this study, a computational algorithm has been developed to automatically detect human face and irises from color images captured by real-time camera. Haar cascade-based algorithm has been applied for simple and fast ...

    • Recognition of human front face in Grayscale Images 

      Mohamed Rizon, Mohamed Juhari; Phaklen Ehkan; Ahmad Nasir, Che Rosli (Kolej Universiti Kejuruteraan Utara Malaysia, 2005-05-18)
      We propose a new technique to recognize the unknown person in grayscale face images for which the position, scale and image-plane rotation of the face are unknown. The proposed system detects the iris of both eyes and ...

    • Various Recognition approach in human faces 

      Karthigayan, M.; Mohd Rizon, Mohamed Juhari; Sazali, Yaacob; Nagarajan, R.; Puteh, Saad; Muhammed Firdaus, Hashim; Haniza, Yazid (Universiti Teknologi Petronas (UTP), 2005-12-01)
      In this paper, we review researches on human faces from aspect offace recognition and face detection. Face emotion recognition are also reviewed. The study of human faces has much assistance on computer vision and machine ...