scholarly journals Fast Facial Detection by Depth Map Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Ming-Yuan Shieh ◽  
Tsung-Min Hsieh

In order to obtain correct facial recognition results, one needs to adopt appropriate facial detection techniques. Moreover, the effects of facial detection are usually affected by the environmental conditions such as background, illumination, and complexity of objectives. In this paper, the proposed facial detection scheme, which is based on depth map analysis, aims to improve the effectiveness of facial detection and recognition under different environmental illumination conditions. The proposed procedures consist of scene depth determination, outline analysis, Haar-like classification, and related image processing operations. Since infrared light sources can be used to increase dark visibility, the active infrared visual images captured by a structured light sensory device such as Kinect will be less influenced by environmental lights. It benefits the accuracy of the facial detection. Therefore, the proposed system will detect the objective human and face firstly and obtain the relative position by structured light analysis. Next, the face can be determined by image processing operations. From the experimental results, it demonstrates that the proposed scheme not only improves facial detection under varying light conditions but also benefits facial recognition.

Author(s):  
Payal Maken

Face recognition has now become one of the interesting fields of research and has received a substantial attention of researchers from all over the world. Face recognition techniques has been mostly used in the discipline of image analysis, image processing, etc. One of the face recognition techniques is used to develop a face recognition system to detect a human face in an image. In face recognition system a digital image with a human face is given as an input which extracts the significant features of face such as (eyes, nose, chin, cheeks, etc) to recognize a face in a digital image which is an exhausting task. Security of information is very salient feature and is difficult to achieve. Security cameras are present in offices, universities, banks, ATMs, etc. All these security cameras are embedded with face recognition systems. There are various algorithms which are used to solve this problem. This paper provides an overview of various techniques which are often used for this face recognition in a face recognition system. This paper is divided into five parts, first section concludes various face detection techniques, second section describes about image processing ,third section have details about face recognition techniques, fourth section describes various classification methods and last section concludes all of these sections.


1999 ◽  
Vol 09 (PR2) ◽  
pp. Pr2-161
Author(s):  
F. H. Julien ◽  
P. Boucaud ◽  
S. Sauvage ◽  
O. Gauthier-Lafaye ◽  
Z. Moussa

2009 ◽  
Vol 8 (3) ◽  
pp. 887-897
Author(s):  
Vishal Paika ◽  
Er. Pankaj Bhambri

The face is the feature which distinguishes a person. Facial appearance is vital for human recognition. It has certain features like forehead, skin, eyes, ears, nose, cheeks, mouth, lip, teeth etc which helps us, humans, to recognize a particular face from millions of faces even after a large span of time and despite large changes in their appearance due to ageing, expression, viewing conditions and distractions such as disfigurement of face, scars, beard or hair style. A face is not merely a set of facial features but is rather but is rather something meaningful in its form.In this paper, depending on the various facial features, a system is designed to recognize them. To reveal the outline of the face, eyes, ears, nose, teeth etc different edge detection techniques have been used. These features are extracted in the term of distance between important feature points. The feature set obtained is then normalized and are feed to artificial neural networks so as to train them for reorganization of facial images.


Author(s):  
Xiaolin Tang ◽  
Xiaogang Wang ◽  
Jin Hou ◽  
Huafeng Wu ◽  
Ping He

Introduction: Under complex illumination conditions such as poor light sources and light changes rapidly, there are two disadvantages of current gamma transform in preprocessing face image: one is that the parameters of transformation need to be set based on experience; the other is the details of the transformed image are not obvious enough. Objective: Improve the current gamma transform. Methods: This paper proposes a weighted fusion algorithm of adaptive gamma transform and edge feature extraction. First, this paper proposes an adaptive gamma transform algorithm for face image preprocessing, that is, the parameter of transformation generated by calculation according to the specific gray value of the input face image. Secondly, this paper uses Sobel edge detection operator to extract the edge information of the transformed image to get the edge detection image. Finally, this paper uses the adaptively transformed image and the edge detection image to obtain the final processing result through a weighted fusion algorithm. Results: The contrast of the face image after preprocessing is appropriate, and the details of the image are obvious. Conclusion: The method proposed in this paper can enhance the face image while retaining more face details, without human-computer interaction, and has lower computational complexity degree.


2021 ◽  
Vol 13 (12) ◽  
pp. 6900
Author(s):  
Jonathan S. Talahua ◽  
Jorge Buele ◽  
P. Calvopiña ◽  
José Varela-Aldás

In the face of the COVID-19 pandemic, the World Health Organization (WHO) declared the use of a face mask as a mandatory biosafety measure. This has caused problems in current facial recognition systems, motivating the development of this research. This manuscript describes the development of a system for recognizing people, even when they are using a face mask, from photographs. A classification model based on the MobileNetV2 architecture and the OpenCv’s face detector is used. Thus, using these stages, it can be identified where the face is and it can be determined whether or not it is wearing a face mask. The FaceNet model is used as a feature extractor and a feedforward multilayer perceptron to perform facial recognition. For training the facial recognition models, a set of observations made up of 13,359 images is generated; 52.9% images with a face mask and 47.1% images without a face mask. The experimental results show that there is an accuracy of 99.65% in determining whether a person is wearing a mask or not. An accuracy of 99.52% is achieved in the facial recognition of 10 people with masks, while for facial recognition without masks, an accuracy of 99.96% is obtained.


2012 ◽  
Vol 18 (1) ◽  
pp. 531-540 ◽  
Author(s):  
Jens Biegert ◽  
Philip K. Bates ◽  
Olivier Chalus

Author(s):  
Д.А. Смирнов ◽  
В.Г. Бондарев ◽  
А.В. Николенко

Проведен краткий анализ как отечественных, так и зарубежных систем межсамолетной навигации. В ходе анализа были отражены недостатки систем межсамолетной навигации и представлен актуальный подход повышения точности системы навигации за счет применения системы технического зрения. Для определения местоположения ведущего самолета предлагается рассмотреть в качестве измерительного комплекса систему технического зрения, которая способна решать большой круг задач на различных этапах, в частности, и полет строем. Систему технического зрения предлагается установить на ведомом самолете с целью измерения всех параметров, необходимых для формирования автоматического управления полетом летательного аппарата. Обработка изображений ведущего самолета выполняется с целью определения координат трех идентичных точек на фоточувствительных матрицах. Причем в качестве этих точек выбираются оптически контрастные элементы конструкции летательного аппарата, например окончания крыла, хвостового оперения и т.д. Для упрощения процедуры обработки изображений возможно использование полупроводниковых источников света в инфракрасном диапазоне (например, с длиной волны λ = 1,54 мкм), что позволяет работать даже в сложных метеоусловиях. Такой подход может быть использован при автоматизации полета строем более чем двух летательных аппаратов, при этом необходимо только оборудовать системой технического зрения все ведомые самолеты группы The article provides a brief analysis of both domestic and foreign inter-aircraft navigation systems. In the course of the analysis, we found the shortcomings of inter-aircraft navigation systems and presented an up-to-date approach to improving the accuracy of the navigation system through the use of a technical vision system. To determine the location of the leading aircraft, we proposed to consider a technical vision system as a measuring complex, which is able to solve a large range of tasks at various stages, in particular, flight in formation. We proposed to install the technical vision system on the slave aircraft in order to measure all the parameters necessary for the formation of automatic flight control of the aircraft. We performed an image processing of the leading aircraft to determine the coordinates of three identical points on photosensitive matrices. Moreover, we selected optically contrasting elements of the aircraft structure as these points, for example, the end of the wing, tail, etc. To simplify the image processing procedure, it is possible to use semiconductor light sources in the infrared range (for example, with a wavelength of λ = 1.54 microns), which allows us to work even in difficult weather conditions. This approach can be used when automating a flight in formation of more than two aircraft, while it is only necessary to equip all the guided aircraft of the group with a technical vision system


2013 ◽  
Vol 6 (1) ◽  
pp. 267-285 ◽  
Author(s):  
Corey N. Stedwell ◽  
Johan F. Galindo ◽  
Adrian E. Roitberg ◽  
Nicolas C. Polfer

Author(s):  
Mayank Srivastava ◽  
Jamshed M Siddiqui ◽  
Mohammad Athar Ali

The rapid development of image editing software has resulted in widespread unauthorized duplication of original images. This has given rise to the need to develop robust image hashing technique which can easily identify duplicate copies of the original images apart from differentiating it from different images. In this paper, we have proposed an image hashing technique based on discrete wavelet transform and Hough transform, which is robust to large number of image processing attacks including shifting and shearing. The input image is initially pre-processed to remove any kind of minor effects. Discrete wavelet transform is then applied to the pre-processed image to produce different wavelet coefficients from which different edges are detected by using a canny edge detector. Hough transform is finally applied to the edge-detected image to generate an image hash which is used for image identification. Different experiments were conducted to show that the proposed hashing technique has better robustness and discrimination performance as compared to the state-of-the-art techniques. Normalized average mean value difference is also calculated to show the performance of the proposed technique towards various image processing attacks. The proposed copy detection scheme can perform copy detection over large databases and can be considered to be a prototype for developing online real-time copy detection system.   


Sign in / Sign up

Export Citation Format

Share Document