Browsing Conference Papers by Author "paul@unimap.edu.my"

Now showing items 1-20 of 26

    • Active stereo vision based system for estimation of Mobile Robot Orientation using composition matrix 

      Paulraj, Murugesapandian; Fadzilah, Hashim; R. Badlishah, Ahmad; Hema, Chengalvarayan Radhakrishnamurthy; Abdul Hamid, Adom (Universiti Malaysia Perlis, 2009-10-11)
      The computation of a mobile robot position and orientation is a common task in the area of computing vision and image processing. For a successful application, it is important that the position and orientation of a mobile ...

    • Application-specific multichannel EEG data acquisition system for portable biomedical application 

      Paulraj, Murugesa Pandian, Dr.; Abdul Hamid, Adom, Prof. Dr.; Tung, Kai Xu; Subramaniam, Kamalraj (Malaysian Technical Universities Network (MTUN), 2012-11-20)
      This paper presents the design and construction of a low power application-specific EEG bio-potential multichannel amplifier with high common mode rejection ratio (CMRR) and high input impedance. The bio-potential amplifier ...

    • Automatic detection of voice disorders using self loop architecture in back propagation network 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (Anna University, 2008-01-04)
      Acoustic analysis is a non-invasive technique to detect the voice disorders and diagnose the vocal and voice disease. In the recent years, voice disease are increasing dramatically due to unhealthy social habits and voice ...

    • Classification of EEG colour imagination tasks based BMI using energy and entropy features 

      Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Hema, Chengalvarayan Radhakrishnamurthy; Purushothaman, Divakar (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      Electroencephalogram (EEG) signals are the electrophysiological measures of brain function and it is used to develop a brain machine interface. Brain machine interface (BMI) system is used to provide a communication and ...

    • Color recognition algorithm using a neural network model in determining the ripeness of a Banana 

      Paulraj, Murugesapandian; Hema, Chengalvarayan Radhakrishnamurthy; R. Pranesh, Krishnan; Siti Sofiah, Mohd Radzi (Universiti Malaysia Perlis, 2009-10-11)
      This paper presents a simple color recognition algorithm using a Neural Network model and applied to determine the ripeness of a banana. The captured image of the banana is resized and its RGB color components are extracted. ...

    • Control brain machine interface for a power wheelchair 

      Hema, Chengalvarayan Radhakrishnamurthy; Murugesa Pandiyan, Paulraj, Assoc. Prof. Dr. (Springer-Verlag, 2011-06-20)
      Controlling a power wheelchair using a brain machine interface (BMI) requires sufficient subject training. A neural network based BMI design using motor imagery of four states is used to control the navigation of a power ...

    • Damage detection in steel plates using discrete cosine transformation techniques and artificial neural network 

      Paulraj, M.P.; Mohd Shukry, Abdul Majid; Sazali, Yaacob; Mohd Hafiz, Fazalul Rahiman; R Pranesh, Krishnan (Universiti Malaysia Perlis, 2009-10-11)
      In this paper, a simple method for crack identification in steel plates based on the Frame Energy based Discrete Cosine Transformation [DCT] moments is presented. A simple experimental procedure is also proposed to measure ...

    • Diagnosis of voice disorders using band energy spectrum in wavelet domain 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Muthusamy, Hariharan, Dr. (Universiti Malaysia Perlis (UniMAP), 2008-03-08)
      In the evolution of quality of speech, acoustic analyses of normal and pathological voices have become increasingly interesting to researchers in laryngology and speech pathologies. Vocal signal information plays an important ...

    • Discrimination of pathological voices using systole activated neural network 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Hariharan, Muthusamy, Dr. (Noise, Vibration and Comfort Research Group, 2007-11-27)
      The discrimination of normal and pathological voices using noninvasive acoustical analysis features helps speech specialits to perform accurate diagnoses of vocal and voices disease. Acoustic analysis is a non-invasive ...

    • Feature extraction based on mel-scaled wavelet packet transform for the diagnosis of voice disorders 

      Murugesa Pandian, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Muthusamy, Hariharan, Dr. (SpringerLink, 2008-06-25)
      Feature extraction from the vocal signal plays very important role in the area of automatic detection of voice disorders. Many feature extraction algorithms have been developed in the last three decades based on acoustic ...

    • Highways Traffic Surveillance System (HTSS) using OpenCV 

      Zainab Nazar, Khalil Wafi; R. Badlishah, Ahmad, Prof. Madya, Dr.; Paulraj, Murugesa Pandiyan, Prof. Madya Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2010-06-22)
      Due to the traffic accidents over the last few years; the development of surveillance systems with multifunctional techniques has received increasing attention. The use of the smart camera is one solution to solve the ...

    • Identification of vocal and voice disorders 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Rizon, Mohammed Juhari, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (Universiti Malaysia Perlis (UniMAP), 2007-10-25)
      The discrimination of normal and pathological voices using noninvasive acoustic analysis helps to perform accurate identification of voice disorders and diagnoses of vocal and voice disease. Acoustic analysis is a non- ...

    • Image quality assessment using Elman neural network model 

      Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Palaniappan, Rajkumar; Mohd Shuhanaz, Zanar Azalan (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      Measurement of visual quality is of fundamental importance for numerous image and video processing applications, where the goal of quality assessment algorithms is to automatically assess the quality of images or videos ...

    • Implementing eigen features methods/neural network for EEG signal analysis 

      Saidatul Ardeenawatie, Awang; Pandiyan, Paulraj Murugesa, Prof. Dr.; Sazali, Yaacob, Prof. Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2013-01)
      This paper presented the possibility of implementing eigenvector methods to represent the features of electroencephalogram signal. In this study, three eigenvector methods were investigated namely Pisarenko, Multiple Signal ...

    • Moving vehicle identification using artificial neural network 

      Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Siti Marhainis, Othman; Sundararaj, Sathish Kumar (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      Hearing impaired people cannot distinguish the sound from a moving vehicle approaching from their behind. They often face a risky situation while they are in outdoors. In this paper, a simple algorithm is proposed to ...

    • Moving vehicle noise classification using backpropagation algorithm 

      Norasmadi, Abdul Rahim; Paulraj, Murugesa Pandiyan, Assoc. Prof.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Sundararaj, Sathishkumar (Institute of Electrical and Electronics Engineers (IEEE), 2010-05-21)
      The hearing impaired is afraid of walking along a street and living a life alone. Since it is difficult for hearing impaired to hear and judge sound information and they often encounter risky situations while they are in ...

    • Moving vehicle recognition and classification based on time domain approach 

      Paulraj, Murugesa Pandian, Dr.; Abdul Hamid, Adom, Prof., Dr.; Sundararaj, Sathishkumar; Norasmadi, Abdul Rahim (Malaysian Technical Universities Network (MTUN), 2012-11-20)
      Differentially Hearing Ability Enabled (DHAE) community cannot discriminate the sound information from a moving vehicle approaching from their behind. This research work is mainly focused on recognition of different vehicles ...

    • Neural network based detection of voice disorders using energy spectrum and equal-loudness contours 

      Murugesa Pandian, Paulraj, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (Universiti Teknologi MARA (UiTM)Faculti of Electrical Engineering, 2008-03-07)
      Impairment of vocal function can have a major impact on the quality of life, severely limiting communication at work and affecting all social aspect of daily life. In the recent years, voice disease are increasing dramatically ...

    • A phoneme based sign language recognition system using interleaving feature and neural network 

      Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Shuhanaz, Zanar Azalan; Palaniappan, Rajkumar (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      A sign language is a language which, instead of acoustically conveyed sound patterns, uses visually transmitted sign patterns. Sign languages are commonly developed in hearing impaired communities, which can include ...

    • Phoneme-based or isolated-word modeling speech recognition system? An overview 

      Yusnita, M. A.; Murugesa Pandiyan, Paulraj, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Shahriman, Abu Bakar; Saidatul Ardeenaawatie, Awang; Ahmad Nazri, Abdullah (Institute of Electrical and Electronics Engineers (IEEE), 2011-03-04)
      In this paper speech theories and some methodological concerns about feature extraction and classification techniques widely used in speech recognition system are surveyed and discussed. The shortage of isolated word speech ...