The Utilization of Feature based Viola-Jones Method for Face Detection in Invariant Rotation

Abstract

Faces in an image consists of complex structures in object detection. The components of a face, which includes the eyes, nose and mouth of a person differs from that of ordinary objects, thus making face detecting a complex process. Some of the challenges encounter posed in face detection of unconstrained images includes background variation, pose variation, facial expression, occlusion and noise. Current research of Viola-Jones (V-J) face detection is limited to only 45 degrees in-plane rotation. This paper proposes only one technique for the V-J detection face in unconstrained images, which V-J face detection with invariant rotation. The technique begins by rotating the given image file with each step 30 degrees until 360 degrees. Each step of adding 30 degrees from origin, V-J face detection is applied, which covers more angles of a rotated face in unconstrained images. Robust detection in rotation invariant used in the above techniques will aid in the detecting of rotated faces in images. The images that have been utilized for testing and evaluation in this paper are from CMU dataset with 12 rotations on each image. Therefore, there are 12 test patterns generated. These images have been measured through the correct detection rate, true positive and false positive. This paper shows that the proposed V-J face detection technique in unconstrained images have the ability to detect rotated faces with high accuracy in correct detection rate. To summarize, V-J face detection in unconstrained images with proposed variation of rotation is the method utilized in this paper. This proposed enhancement improves the current V-J face detection method and further increase the accuracy of face detection in unconstrained images.

Authors and Affiliations

Tioh Keat Soon, Abd Samad Hasan Basari, Nuzulha Khilwani Ibrahim, Burairah Hussin, Ariff Idris, Noorayisahbe Mohd Yaacob, Mustafa Almahdi Algaet, Norazira A. Jalil

Keywords

Related Articles

Description Logic Application for UML Class Diagrams Optimization

Most of known technologies of object-oriented developments are UML-based; particularly widely used class diagrams that serve to describe the model of a software system, reflecting the regularities of the domains. CASE to...

Opinion Mining: An Approach to Feature Engineering

Sentiment Analysis or opinion mining refers to a process of identifying and categorizing the subjective information in source materials using natural language processing (NLP), text analytics and statistical linguistics....

Identification and Formal Representation of Change Operations in LOINC Evolution

LOINC (Logical Observation Identifiers Names and Codes) is one of the standardized health ontologies that is widely used by practitioners in the health sector. Like other ontologies in health field, LOINC evolves. This r...

Expectation-Maximization Algorithms for Obtaining Estimations of Generalized Failure Intensity Parameters

This paper presents several iterative methods based on Stochastic Expectation-Maximization (EM) methodology in order to estimate parametric reliability models for randomly lifetime data. The methodology is related to Max...

Efficient Verification-Driven Slicing of UML/OCL Class Diagrams

Model defects are a significant concern in the Model-Driven Development (MDD) paradigm, as model trans-formations and code generation may propagate errors present in the model to other notations where they are harder to...

Download PDF file
  • EP ID EP429118
  • DOI 10.14569/IJACSA.2018.091211
  • Views 84
  • Downloads 0

How To Cite

Tioh Keat Soon, Abd Samad Hasan Basari, Nuzulha Khilwani Ibrahim, Burairah Hussin, Ariff Idris, Noorayisahbe Mohd Yaacob, Mustafa Almahdi Algaet, Norazira A. Jalil (2018). The Utilization of Feature based Viola-Jones Method for Face Detection in Invariant Rotation. International Journal of Advanced Computer Science & Applications, 9(12), 73-78. https://europub.co.uk/articles/-A-429118