CreateSpace Independent Publishing Platform, 2016. — 123 p. — ISBN-10: 151518370X. — ISBN-13: 978-1515183709Face recognition become very interesting topic of research because of lot of unsolved parameters. From past few decades number of researchers work on the topic to solve the problem of face recognition but still successful face recognition system is not yet implemented hence we proposed face recognition algorithm that match face matrix. As discuss face is nothing but a matrix so using MATLAB software we do matrix manipulation and try to find best possible features for face recognition. In law enforcement and lot of commercial applications, such as in the area of access control systems, national identity, video surveillance, user authentication and retrieval of identity from a data base for criminal investigations face recognition play very important roll but due to challenging problem in real time applications it is not so user friendly. We take look on many unsolved parameters, such as face illumination, expression, pose, scale, low resolution, partial face (occlusion) and other environmental conditions, night video footage and day video footage. However, different pose and occlusion remains as major challenges in face recognition and these two problems affect the performance of face recognition in access control, authentication, and surveillance applications. To meet these challenges, the present study proposed a face recognition system using the analytical approach in which centre of two eye i.e. forehead used for feature extraction. In existing methods of analytical face recognition systems, features like eyes, nose, mouth where used as feature point but in proposed system we used forehead region maximum face recognition rate is 80% using Lab view software. In proposed analytical approach of face recognition, no any work has been done using above mention features but by using different features very little work had done. In literature study maximum recognition rate of analytical, holistic and hybrid approach is below 84% using different face database. In proposed SKM forehead feature work enhancement in recognition rates to 86% and require less time and also solve two big challenges half occlusion and different pose. Facial recognition system is a most useful computer application or device that can identify individuals based on their unique facial characteristics. Unlike many other biometric identification methods (e.g., fingerprints, voiceprint, speech), this can be advantageous in clean environments, for surveillance or tracking, and in automation systems. Because the system keeps a reference model of the individual, and captures their image for identification. They may also be more error-prone when identifying individuals, due to the fairly recent development of the technology. As we know lot of literature available on websites, books, journal etc, we consider international and national paper survey for primary source of data. Various algorithm studies is done from this information collected analysis will be done using various parameters to achieve the basic objective. Study of most popular appearance based face recognition projection methods and detailed descriptions of each module are studied. Our ID cards, passwords can be lost but face is connected part of our body so he/she can be verified with the help of their face. Recently face recognition is attracting much attention in the society of network multimedia information access & also for security purpose. We are providing an up-to-date critical survey of image - and video-based face recognition research. There are two things for us to write this thesis first is to provide an up-to-date review of the existing literature available on net, and the second is to offer some insights into the studies of machine recognition of faces using software. We conclude the thesis with proposed KSM algorithm that helps the government and private sector for security purpose

CreateSpace独立出版平台，2016年。- 123页 - ISBN-10: 151518370X. - ISBN-13: 978-1515183709人脸识别成为非常有趣的研究主题，因为有很多未解决的参数。在过去的几十年里，许多研究人员致力于解决人脸识别的问题，但仍然没有成功的人脸识别系统，因此我们提出了匹配人脸矩阵的人脸识别算法。由于讨论的是人脸只不过是一个矩阵，所以我们使用MATLAB软件进行矩阵处理，并试图找到人脸识别的最佳特征。在执法和许多商业应用中，例如在门禁系统、国民身份、视频监控、用户认证和从刑事调查数据库中检索身份等领域，人脸识别发挥着非常重要的作用，但由于实时应用中的挑战性问题，它并不那么容易使用。我们研究了许多未解决的参数，如面部照明、表情、姿势、比例、低分辨率、部分面部（遮挡）和其他环境条件、夜间录像和白天录像。然而，不同的姿势和遮挡仍然是人脸识别的主要挑战，这两个问题影响了人脸识别在访问控制、认证和监控应用中的表现。为了应对这些挑战，本研究提出了一个使用分析方法的人脸识别系统，其中两只眼睛的中心即额头被用于特征提取。在现有的分析性人脸识别系统中，眼睛、鼻子、嘴巴等特征被用作特征点，但在拟议的系统中，我们使用额头区域，使用Lab view软件，最大的人脸识别率为80%。在拟议的分析性人脸识别方法中，没有使用上述特征的工作，但通过使用不同的特征做了很少的工作。在文献研究中，使用不同的人脸数据库，分析法、整体法和混合法的最大识别率都低于84%。在提议的SKM额头特征工作中，识别率提高到了86%，并且需要更少的时间，还解决了半遮挡和不同姿势这两大挑战。面部识别系统是一种最有用的计算机应用或设备，可以根据个人独特的面部特征来识别他们。与许多其他生物识别方法（如指纹、声纹、语音）不同，这在清洁环境、监视或跟踪以及自动化系统中都是有利的。因为系统会保留个人的参考模型，并捕捉其图像进行识别。由于该技术发展较晚，它们在识别个人时也可能更容易出错。由于我们知道网站、书籍、杂志等有很多文献，我们考虑将国际和国内的论文调查作为主要数据来源。各种算法的研究是从这些收集到的信息中完成的，分析将使用各种参数来实现基本目标。研究最流行的基于外观的人脸识别投影方法和每个模块的详细描述。我们的身份证、密码可能会丢失，但脸是我们身体的一部分，所以他/她可以通过脸的帮助来验证。最近，人脸识别在网络多媒体信息访问和安全方面引起了社会的广泛关注。我们正在提供一个最新的基于图像和视频的人脸识别研究的重要调查。我们写这篇论文有两个目的，第一是对网上现有的文献提供一个最新的回顾，第二是对使用软件的人脸机器识别的研究提供一些见解。在论文的最后，我们提出了KSM算法，该算法有助于政府和私营部门的安全。