NEURAL NETWORK CORRELATION BASED SIMILARITY EVALUATION WITH ZERNIKE MOMENTS FOR THE POSE-INVARIANT FACE RECOGNITION

Abstract

Human face recognition is best application in pattern recognition for identification and recognition. Development of face recognition system is increasing day by day in market and research organizations. Different parameters and methods are used for face recognition. In this research project, we will discuss about the different algorithms used for face recognition that are Zernike Moments (ZMs) and correlation classification (CC) etc and compare these algorithms with proposed algorithm Z_CC (Zernike with Correlation Classification).The angular information or rotation of the face is calculated by using the Zernike moments (ZM) to obtain the degree or radian of face rotation from the frontal view. The robust combination of angle-invariant and scale-invariant features with the combination of Zernike moments and correlation classification has been proposed with the neural network classification. The experiments will be performed on the variety of datasets. The multi-object dataset has been combined by collection the samples with faces rotated in the training samples. Z_NN (Zernike with neural network) algorithm provide best recognition rate for human face recognition 90%. In this algorithm we use Zernike Moments and correlation for global feature extraction and after that these features are compared by using neural network.

Authors and Affiliations

Priya Thakur

Keywords

Related Articles

PERFORMANCE ANALYSIS OF INTEGRATED PACKED BED SOLAR FLAT PLATE COLLECTOR

The main objective of this paper is to study the performance of a solar flat plate collector - packed bed system by using various secondary working fluids such as water, air. In the pr...

 ENERGY HARVESTER FOR VIBRATION CONTROL AND ELECTRICITY GENERATION

 This paper presents the application of energy harvester for controlling the vibration of marine structures and also at the same time generates the electricity for charging the low power devices. The motivation...

 Efficient Design to Meet High Power Density Applications Using DC-DC Energy Conversion

 Bacteria in marine habitat have modified structure of enzymes, ribosomes, and transport proteins which require high levels of potassium for stability and activity. In the present study, α-amylase producing Breviba...

 Experimental Investigation of Biodiesel Production from Waste Mustard Oil

 The demand for petroleum is increasing with each passing day. This may be attributed to the limited resources of petroleum crude. Hence there is an urgent need of developing alternative energy sources to meet the...

  Accelerometer Based Gesture Driven Embedded System for Differently Abled

 This document proposes an idea of an automated system based on accelerometer which can be very helpful for the differently abled patients. The limited number of pre through automated system and can be used very...

Download PDF file
  • EP ID EP164506
  • DOI 10.5281/zenodo.52503
  • Views 86
  • Downloads 0

How To Cite

Priya Thakur (30). NEURAL NETWORK CORRELATION BASED SIMILARITY EVALUATION WITH ZERNIKE MOMENTS FOR THE POSE-INVARIANT FACE RECOGNITION. International Journal of Engineering Sciences & Research Technology, 5(5), 924-930. https://europub.co.uk/articles/-A-164506