International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 07 | July 2023
p-ISSN: 2395-0072
www.irjet.net
Face Recognition Based on Image Processing in an Advanced Robotic System Amandeep Kaur1, Swati Sharma1, Sumit Asthana1 , Sushil Kumar Pal 1, Anshuman Singh 1, Vishal Kumar 1, Vivek Kumar 1 1Department of Instrumentation, Bhaskaracharya College of Applied Sciences, University of Delhi
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - In the present work, face recognition system has
(iv) Measurement of pattern in an image and (v) Image Recognition – Distinguish the objects in an image [2].
been developed using image processing technique. The system developed works in two stages. In the first stage, face recognition algorithm is used to unlock the system by a valid user face. Once the system is unlocked, then the motion of robot is controlled using different navigation images. Face recognization is implemented using SVM (support vector machine), HOG (histogram of oriented gradients) and kNN (knearest neighbors) algorithm in MATLAB. The whole process is based on the concept called Machine Learning in artificial intelligence. Here we are dealing with supervised machine learning technique where the machine is trained in supervised manner.
In the present work, we will be implementing the (v) part i.e. Face recognition. As we know that face plays a major role in our social intercourse in conveying identity and expressions. The human ability to recognize faces is remarkable. We can recognize thousands of faces learned throughout our lifetime and identify familiar faces at a glance even after years of separation. But developing a computational model of face recognition is quite difficult, because faces are complex, multidimensional, and subject to change over time and integration of face recognition in robotics is more difficult [3-4].
Key Words: Face recognition, SVM, HOG, KNN, Machine learning
Face recognition has its applications in various fields. Machines and technology are increasing rapidly, but we lack a system which can distinguish between different users and respond to that uniquely. Today most of the systems are blind because they cannot differentiate between valid and invalid users. Keeping security breaching in mind, face recognition based system must be developed in order to improve security level. Face recognition is a part of advanced image processing which can be achieved using image processing algorithm as shown in Figure 1[5].
1. INTRODUCTION The field of digital image processing has grown rapidly after 1960, after the development of hi-speed computer. It has found importance in mainly two areas: (i) Improvement of pictorial information for better human interpretation and the second being the processing of a scene data for an autonomous machine perception. The first feature i.e. image enhancement and restoration are used to process degraded or blurred images. As per medical imaging is concerned, most of the images may be used in the detection of tumors or for screening the patients. Whereas second feature i.e. machine perception can be employed in automatic character recognition, industrial machine vision for product assembly and inspection. The continuing decline in the ratio of computer price to performance and the expansion of networking and communication bandwidth via the world wide web and the Internet have created unprecedented opportunities for continued growth of digital image processing [1]. Digital image processing basically includes the following three steps: Importing the image with optical scanner, analyzing and manipulating the image and Output is the last stage in which result can be altered image or report that is based on image analysis. It can be used to perform various tasks such as: (i) Visualization of the objects that are not visible, (ii) Image sharpening and restoration to create a better image, (iii) Image retrieval to seek image of interest,
© 2023, IRJET
|
Impact Factor value: 8.226
Fig 1- Image Processing Flow chart
|
ISO 9001:2008 Certified Journal
|
Page 241