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Author: Nurul Zarina Md Isa Publisher: ISBN: Category : Biometric identification Languages : en Pages : 66
Book Description
In principle, to combine face detection and gender classification methods may seem simple. However, this process is more complex than it appears because requires many aspects for consideration. The gender classification has attracted much attention in psychological literature, relatively few machine vision methods have been proposed. However it has been extensively studied in the context of surveillance applications and biometrics. This project is mainly concern with offline gender classification using purely image processing technique which using a database that was included in the system. The way of doing this is by extracting the differences between male and female facial features. Obviously the classification base on a single feature is not adequate since humans share many facial properties even within different gender group. So multilayer processing is needed. This project is working as expected based on the scope and objective of project. Although not many varieties of facial images have been considered like colored hair the basic techniques should be just the same. For the system classification, Template Matching Technique is used to match image with the database image. The system attempts are made to capture the most appropriate representation of face images as a whole and exploit the statistical regularities of pixel intensity variations. When attempting recognition, the unclassified image is compared with all the database images, returning a vector of matching score. The unknown person is then classified as the one giving the highest cumulative score. This project will be build using the MATLAB software. Overall, the project can be used and developed for various purposes, particularly to expedite the process of searching the database. The refinement of this project in other hand can lead to more accurate and reliable result by considering other facial properties like eyes, nose and eyebrows.
Author: Nurul Zarina Md Isa Publisher: ISBN: Category : Biometric identification Languages : en Pages : 66
Book Description
In principle, to combine face detection and gender classification methods may seem simple. However, this process is more complex than it appears because requires many aspects for consideration. The gender classification has attracted much attention in psychological literature, relatively few machine vision methods have been proposed. However it has been extensively studied in the context of surveillance applications and biometrics. This project is mainly concern with offline gender classification using purely image processing technique which using a database that was included in the system. The way of doing this is by extracting the differences between male and female facial features. Obviously the classification base on a single feature is not adequate since humans share many facial properties even within different gender group. So multilayer processing is needed. This project is working as expected based on the scope and objective of project. Although not many varieties of facial images have been considered like colored hair the basic techniques should be just the same. For the system classification, Template Matching Technique is used to match image with the database image. The system attempts are made to capture the most appropriate representation of face images as a whole and exploit the statistical regularities of pixel intensity variations. When attempting recognition, the unclassified image is compared with all the database images, returning a vector of matching score. The unknown person is then classified as the one giving the highest cumulative score. This project will be build using the MATLAB software. Overall, the project can be used and developed for various purposes, particularly to expedite the process of searching the database. The refinement of this project in other hand can lead to more accurate and reliable result by considering other facial properties like eyes, nose and eyebrows.
Author: Mohammad Esmaeel Mousa Pasandi Publisher: ISBN: Category : University of Ottawa theses Languages : en Pages :
Book Description
This thesis focuses on the area of face processing and aims at designing a reliable framework to facilitate face, age, and gender recognition. A Bag-of-Words framework has been optimized for the task of face recognition by evaluating different feature descriptors and different bag-of-words configurations. More specifically, we choose a compact set of features (e.g., descriptors, window locations, window sizes, dictionary sizes, etc.) in order to produce the highest possible rate of accuracy. Experiments on a challenging dataset shows that our framework achieves a better level of accuracy when compared to other popular approaches such as dimension reduction techniques, edge detection operators, and texture and shape feature extractors. The second contribution of this thesis is the proposition of a general framework for age and gender classification. Although the vast majority of the existing solutions focus on a single visual descriptor that often only encodes a certain characteristic of the image regions, this thesis aims at integrating multiple feature types. For this purpose, feature selection is employed to obtain more accurate and robust facial descriptors. Once descriptors have been computed, a compact set of features is chosen, which facilitates facial image processing for age and gender analysis. In addition to this, a new color descriptor (CLR-LBP) is proposed and the results obtained is shown to be comparable to those of other pre-existing color descriptors. The experimental results indicates that our age and gender framework outperforms other proposed methods when examined on two challenging databases, where face objects are present with different expressions and levels of illumination. This achievement demonstrates the effectiveness of our proposed solution and allows us to achieve a higher accuracy over the existing state-of-the-art methods.
Author: Joni-Kristian Kamarainen Publisher: Springer ISBN: 3642388868 Category : Computers Languages : en Pages : 733
Book Description
This book constitutes the refereed proceedings of the 18th Scandinavian Conference on Image Analysis, SCIA 2013, held in Espoo, Finland, in June 2013. The 67 revised full papers presented were carefully reviewed and selected from 132 submissions. The papers are organized in topical sections on feature extraction and segmentation, pattern recognition and machine learning, medical and biomedical image analysis, faces and gestures, object and scene recognition, matching, registration, and alignment, 3D vision, color and multispectral image analysis, motion analysis, systems and applications, human-centered computing, and video and multimedia analysis.
Author: Ajith Abraham Publisher: Springer ISBN: 3319606182 Category : Technology & Engineering Languages : en Pages : 733
Book Description
This volume presents 70 carefully selected papers from a major joint event: the 8th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016) and the 8th International Conference on Computational Aspects of Social Networks (CASoN 2016). SoCPaR–CASoN 2016, which was organized by the Machine Intelligence Research Labs (MIR Labs), USA and Vellore Institute of Technology (VIT), India and held at the VIT on December 19–21, 2016. It brings together researchers and practitioners from academia and industry to share their experiences and exchange new ideas on all interdisciplinary areas of soft computing and pattern recognition, as well as intelligent methods applied to social networks. This book is a valuable resource for practicing engineers/scientists and researchers working in the field of soft computing, pattern recognition and social networks.
Author: Brijesh Iyer Publisher: Springer Nature ISBN: 9813295155 Category : Technology & Engineering Languages : en Pages : 913
Book Description
The book is a collection of selected high quality research papers presented at the International Conference on Computing in Engineering and Technology (ICCET 2019), held on January 10–11, 2019 at Deogiri Institute of Engineering and Management Studies, Aurangabad, India. Focusing on frontier topics and next-generation technologies, it presents original and innovative research from academics, scientists, students, and engineers alike.
Author: Siddhartha Bhattacharyya Publisher: Springer ISBN: 9811367833 Category : Technology & Engineering Languages : en Pages : 135
Book Description
This book presents fascinating, state-of-the-art research findings in the field of signal and image processing. It includes conference papers covering a wide range of signal processing applications involving filtering, encoding, classification, segmentation, clustering, feature extraction, denoising, watermarking, object recognition, reconstruction and fractal analysis. It addresses various types of signals, such as image, video, speech, non-speech audio, handwritten text, geometric diagram, ECG and EMG signals; MRI, PET and CT scan images; THz signals; solar wind speed signals (SWS); and photoplethysmogram (PPG) signals, and demonstrates how new paradigms of intelligent computing, like quantum computing, can be applied to process and analyze signals precisely and effectively. The book also discusses applications of hybrid methods, algorithms and image filters, which are proving to be better than the individual techniques or algorithms.
Author: Arun Kumar Rana Publisher: CRC Press ISBN: 1000450481 Category : Computers Languages : en Pages : 330
Book Description
Internet of things (IoT) is the connection and communication of physical objects (smart devices) over the internet. In this recent age, people’s daily lives are dependent on the internet through their smartphones, tablets, Smart TVs, micro-controllers, Smart Tags, computers, laptops, and cars to name a few. This book discusses different ways to create a better IoT network and/or IoT platforms to improve the efficiency and quality of these products and subsequently their users' lives. In addition, this book provides future research directions in energy, industry, and healthcare, and explores the different applications of IoT and its associated technologies. It provides an overview and explanation of the software architecture, middleware, data processing and data management as well as security, sensors, actuators and algorithms used to create a working IoT platform. The editors then go on to examine IoT networks and platforms as they relate to energy industry including, energy efficiency and management, intelligent energy management, smart energy through blockchain and energy-efficient/aware routing/scheduling challenges and issues. They then explore IoT as it applies to healthcare including biomedical image and signal analysis and disease prediction and diagnosis. Finally the editors examine the prospects and applications of IoT for industry through the concepts of smart industry, including architecture, blockchain, and Industry 4.0. This book is intended for senior undergraduate and graduate students, researchers and industry professionals working on IoT applications and infrastructure. Reviews IoT software architecture and middleware, data processing and management, security, privacy and reliability, architectures, protocols, technologies, algorithms, and smart objects, sensors, and actuators Explores IoT as it applies to energy, including energy efficiency and management, intelligent energy management, smart energy through blockchain and energy-efficient/aware routing/scheduling challenges and issues Examines IoT as it applies to healthcare including biomedical image and signal analysis, and disease prediction and diagnosis Examines IoT as it applies to smart industry including architecture, blockchain, and Industry 4.0 Discusses different ways to create a better IoT network or IoT platform
Author: Emon Kumar Dey Publisher: LAP Lambert Academic Publishing ISBN: 9783659412097 Category : Languages : en Pages : 80
Book Description
Computer vision-based gender detection from facial image is a challenging and important task for computer vision-based researchers. The automatic gender detection from face image has potential applications in visual surveillance and human-computer interaction sys- tems (HCI). Human faces provide important visual information for gender perception. The system described in this book can automatically detect face from input images and the detected facial area is taken as region of interest (ROI). Some techniques and algorithm of Image Processing is applied on that ROI which identifies the gender of the face image.The experimental reseult described on chapter 4 in this book finds the accuracy of the system is more than 80%.
Author: Nurul Zarina Md Isa
Author: Nurul Zarina Md Isa
Author: Mohammad Esmaeel Mousa Pasandi
Author: Joni-Kristian Kamarainen
Author: Cunjian Chen
Author: Ajith Abraham
Author: Brijesh Iyer
Author: Siddhartha Bhattacharyya
Author: Valentina Emilia Balas
Author: Arun Kumar Rana
Author: Emon Kumar Dey