In the contemporary digital landscape, this project presents an innovative ATM security system that seamlessly integrates face recognition authentication and OTP (One-Time Password) verification, significantly enhanci...
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Everything in the world today is mechanised and connected online. Where everything can be done by machine automatically. Such as it is difficult to deal with the presence of several students in a classroom under the c...
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The airport industry is one of the biggest and busiest industries in the world. It is estimated that more than 3000 million passengers travel worldwide via airplanes in a single year. Airports are often the transit po...
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In this paper, a smart home security system by using local binary pattern histograms (lbph) face detection algorithm is proposed to enhance the security level of entry-system. Face recognition is an interesting but ch...
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ISBN:
(纸本)9781538683033
In this paper, a smart home security system by using local binary pattern histograms (lbph) face detection algorithm is proposed to enhance the security level of entry-system. Face recognition is an interesting but challenging in machine learning field and impacts important applications in many areas such as remote sensing, machine/robot vision, pattern recognition, medical field, banking and security system access, and authentication in personal electronics gadget. In this research paper, we proposed the door lock security system using image processing instead of traditional key and digital lock system. The image processing mainly consists of three parts, namely face representation, feature extraction and identification of face. Face representation represents how to model a face with lbph algorithms of detection and recognition. The most useful and unique features of the face image are extracted in the feature extraction phase. In the identification of face the new face image is compared with the images which are already extracted and saved on database. Face detection and recognition method was applied to allow the authorized dwellers and the guest and prevent unwanted person to enter inside the house.
Face recognition is still one of the most popular biometric recognition techniques. It is widely used, both online and offline. Performance of such a system is directly connected to face image quality. Since blur and ...
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ISBN:
(纸本)9781538669747
Face recognition is still one of the most popular biometric recognition techniques. It is widely used, both online and offline. Performance of such a system is directly connected to face image quality. Since blur and motion blur are common imagery problems, this paper explores the influence of such disturbances on the face recognition performance. The research described in this paper compares the performance of the face recognition algorithm based on the Haar features and Local Binary Patterns Histograms when it uses face images of a good quality, images with added Gaussian blur and motion blur, as well as enhanced images.
Facial identication is important these days, Methods are required must be fast and accurate enough to work realtime. So research in methods for face recognition seems ever growing. The measurements of an individuals d...
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ISBN:
(纸本)9781538640081
Facial identication is important these days, Methods are required must be fast and accurate enough to work realtime. So research in methods for face recognition seems ever growing. The measurements of an individuals data is inherent part of FR techniques. In biomedical verification and identification requires the dataset such as iris, finger prints etc. While for FR, cameras are replacing the cards at places like ATMs. It helps capturing facial images of customers, and compare these photos to the images of account holders database of banks to verify the customers identity. This paper proposes way for face recognition. Shape and texture of facial images are studied for representation. The face is Firstly divided into tiny regions. Which are used to get lbph. These histograms merged in one partially enhanced histogram, by which we get face images effciently. KNN classier does the classication and not just effciency but the simplicity of manner allows very fast feature extraction.
Facial identication is important these days, Methods are required must be fast and accurate enough to work realtime. So research in methods for face recognition seems ever growing. The measurements of an individuals d...
详细信息
Facial identication is important these days, Methods are required must be fast and accurate enough to work realtime. So research in methods for face recognition seems ever growing. The measurements of an individuals data is inherent part of FR techniques. In biomedical verification and identification requires the dataset such as iris, finger prints etc. While for FR, cameras are replacing the cards at places like ATMs. It helps capturing facial images of customers, and compare these photos to the images of account holders database of banks to verify the customers identity. This paper proposes way for face recognition. Shape and texture of facial images are studied for representation. The face is Firstly divided into tiny regions. Which are used to get lbph. These histograms merged in one partially enhanced histogram, by which we get face images effciently. KNN classier does the classication and not just effciency but the simplicity of manner allows very fast feature extraction.
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