Browsing Paulraj Murugesa Pandiyan, Assoc. Prof. Dr. by Author "Mohd Shuhanaz, Zanar Azalan"

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    • 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 ...

    • 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 ...

    • A phoneme based sign language recognition system using skin color segmentation 

      Paulraj, Murugesa Pandiyan, Prof. Madya; Sazali, Yaacob, Prof. Dr.; Mohd Shuhanaz, Zanar Azalan; Palaniappan, Rajkumar (Institute of Electrical and Elctronics Engineering (IEEE), 2010-05-21)
      A sign language is a language which, instead of acoustically conveyed sound patterns, uses visually transmitted sign patterns. Sign languages are commonly developed for deaf communities, which can include interpreters, ...

    • A simple sign language recognition system using affine moment blur invariant features 

      Rajkumar, Palaniappan; Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Shuhanaz, Zanar Azalan (Universiti Malaysia Perlis (UniMAP)Centre for Graduate Studies, 2010-10-16)
      Sign language recognition is one of the most promising sub-fields in gesture recognition research. Effective sign language recognition would grant the deaf and hard-of-hearing expanded tools for communicating with both ...