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In recent years, face detection is widely used in various fields, such as face recognition, image focusing, and surveillance systems. This study proposes a real-time face detection system based on naive Bayesian classifier using Field-programmable gate array(FPGA). The detection system divided into three main parts, feature extraction, candidate face detection, and false elimination. First, downscale...
Face recognition is an important biometric tool due to contact independence. In real time scenarios such as criminal record databases, it is vital to provide the user with high accuracy results in reasonable time. Compared to the software counter parts, the existing hardware solutions on FPGAs provide higher accuracy. However, such systems are not scalable due to high resource utilization (i.e. number...
This paper gives the hardware implementation of face detection on FPGA using Haar features. The design consisting of integral image generation which is used to compute the Haar features at a faster rate, has been illustrated. The classifiers are built using the AdaBoost algorithm which selects a minimum number of critical Haar features from a very large set. Also, parallel processing classifiers increase...
The need for facial recognition systems that are fast and accurate is continuously increasing. In this paper, a face recognition implementation on a System on Chip (SoC), integrated with an FPGA, is presented. This implementation utilizes Local Binary Patterns Histograms to extract features from test face images and Manhattan distance to retrieve the correct match from the system's face database....
Face recognition system is an application for identifying a person from the pool of images. Face detection is an application for detecting objects, analyzing the face, understanding the localization of the face and face recognition. The main goal of the work is to identity the face from a given database images. The face images have similar geometrical features and hence discriminating one face from...
Face recognition is gaining more importance in today's real world for automated transactions. In this paper, we propose FPGA Implementation of Face Recognition System using Efficient 5/3 2D-Lifting scheme. The database image of FVC-2004 DB3_A is resized to 256×256 pixels. The resized image is convolved with 3×3 Gaussian mask kernelsto remove high frequency edges, which improves matching accuracy....
This paper presents a new hardware architecture for pattern detection and classification specific for human face detection including raw image acquisition, integral image creation, window extraction, pyramid generation, and detection algorithms in simultaneous steps. The detection part of the face is implemented in a reconfigurable way by providing different paths for either Viola-Jones or block LBP...
Face recognition system plays an important role in many applications such as surveillance, biometrics and security. In this paper, we present a FPGA implementation of real-time face recognition engine consists of face detection, eye detection and feature extraction/verification module. We apply Self-Quotient Image (SQI) to reduce illumination effect. Haar-AdaBoost trained classifiers are applied for...
Obtaining a real-time implementation for a face detection system is the first step towards human-machine interaction. This paper presents an architecture, implementable on an FPGA, for accelerating the Haar-based face detection algorithm through use of multiple dedicated processing units by utilizing the inherent parallelism in the algorithm. The architecture is designed to be scalable and the face...
This paper presents a simple and efficient design of a face recognition system, where feature extraction algorithm is employed based on the principle of spatial cross-correlation. In the feature extraction process, instead of processing the entire image at a time, only a pair of rows or columns of an image is considered which makes the algorithm very efficient and low-cost. Considering the cross-correlations...
In recent years the use of real-time face detection and face recognition for surveillance, human-machine interfaces and other applications has increased and thus the need for high power, low cost implementations has been posed. In embedded implementations, the computing power needed for face detection system calls for a custom designed processor. In this paper we will discuss implementations of alternatives...
Face detection is a technique that determines the locations and sizes of human face images. It detects facial features and ignores anything else, such as buildings, trees and bodies. Face-detection algorithms focused on the detection of frontal human faces, whereas newer algorithms attempt to solve the more general and difficult problem of multi-view face detection. This paper presents a hardware...
In this communication a speed optimized implementation of Viola-Jones Face Detection Algorithm based on the baseline OpenCV face detection application is presented. The baseline OpenCV face detection application is analyzed. Then the necessary modifications and improvements are described in order to accelerate the execution speed in an embedded or SoC (System-on-Chip) environments.
This paper proposes techniques for face detection and gives the implementation details for an FPGA development board. We analyze and discuss the relation between the system computation cost and selection of the image scaling factor. We give a new method to select the stop threshold for the image reduction process, which reduces the total computation by half. We also provide a color image output mode...
This paper develops a hardware-efficient color segmentation algorithm that is especially suitable to implement on hardware for face detection. Since the modulized design is adopted in the proposed algorithm without floating-point operation, the computational cost is directly reduced for hardware design. The proposed algorithm consists of a color space modeling module and a feature enhancement module...
Assault and robbery on the public transport is a social problem. Almost every day, people lose possessions and, in some cases, thieves or citizens get hurt or even die, in the process. In Mexico, attempts to reduce or prevent crime include vigilance by armed agents [1] and video cameras on public transport [2]. This work contributes to crime reduction and/or prevention on public transport by taking...
Real-time image recognition at 1000 fps is realized by implementing a parallel processing circuit module to calculate higher-order local auto-correlation (HLAC) features on a high-speed vision platform. The circuit module is compactly designed in order to decrease the number of multiplications required in the HLAC calculation. The circuit module is integrated on a user-specific FPGA of the high-speed...
Face detection is the cornerstone of a wide range of applications such as video surveillance, robotic vision and biometric authentication. One of the biggest challenges in face detection based applications is the speed at which faces can be accurately detected. In this paper, we present a novel SoC (System on Chip) architecture for ultra fast face detection in video or other image rich content. Our...
To address the challenges on non-cooperative long-distance human identification and verification, we propose an innovative cost-efficient system for automatic long-range biometric recognition of non-cooperative individuals in 24/7 operations. The system has three cameras. One is a wide field of view (WFOV) CCD video camera with an Infrared (IR) filter and powerful IR illuminators for human scan in...
The face detection is a fundamental prerequisite step in the process of face recognition. The focus of this paper is the implementation of a real time embedded face detection system while relying on high level description language such as SystemC. Recently, the boosting based object detection algorithms proposed by have gained a lot of attention and are considered as the fastest accurate object detection...
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