Classification of Facial Images into Adult or Minor Categories using Facial Features
Harsh Modi1, Daniyah Ammarah2, Aditya Rai3, Sweta Jain4
1Harsh Modi, Former Undergraduate Student, Shri Ramdeobaba College of Engineering and Management, Nagpur, Maharashtra, India.
2Daniyah Ammarah, Former Undergraduate Student, Shri Ramdeobaba College of Engineering and Management, Nagpur, Maharashtra, India.
31Aditya Rai, Former Undergraduate Student, Shri Ramdeobaba College of Engineering and Management, Nagpur, Maharashtra, India.
4Sweta Jain, Assistant Professor, Computer Science Department, Shri Ramdeobaba College of Engineering and Management, Nagpur, Maharashtra, India.
Manuscript received on 04 August 2019 | Revised Manuscript received on 10 August 2019 | Manuscript published on 30 August 2019 | PP: 3949-3952 | Volume-8 Issue-10, August 2019 | Retrieval Number: J99300881019/19©BEIESP | DOI: 10.35940/ijitee.J9930.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Facial images have always been used for various analytical and research purposes as they contain abundant information about personal characteristics, including identity, emotional expression, gender, age, etc. A human image is often defined as a complex signal composed of many facial attributes such as skin colour and geometric facial features. Nowadays the real-world applications of facial images have brought in a new dawn in the field of biometrics, security and surveillance, and these attributes play a crucial role in the same. Unrestricted and unintended access to certain resources and information to the minors has a history of physical and psychological implications, which makes age, in particular, more significant among these attributes. Consider a scenario where users may require an age‐specific human computer interaction system that can estimate age for secure system access control or intelligence gathering. Automatic human age estimation using facial image analysis will come as a rescue with its potential applications in the field of Age Specific Human Computer Interactions and numerous real‐world applications which include human computer interaction and multimedia communication. Here, we aim to identify and classify images provided as input into two main categories, adults and minors. This classification would act as an access controller to the desired resources or information. MATLAB was used to identify the younger and older images. Initially we got the databases of features extracted from the input images using different feature extraction methods. Later we compared the several trained databases to get a specific range for younger and older images. This range then became the basis for identifying the young and the old.
Index Terms: Classification, Feature Analysis, Human- Computer Interaction, Security, Surveillance
Scope of the Article: Classification