Description
Real-time Face Detection using OpenCV -The project is based on face detection using the Haar cascade algorithm. The proposed system involves face detection and Features extraction. Face detection is to detect faces based on a haar cascade algorithm using the python toolbox.? In the feature extraction stage, the GLCM is used for different object textures and edge contour feature extraction processes. A DWT computes the edge response values in all eight directions at each pixel position and generates a code from the relative strength magnitude. The proposed features retain the contrast information of image patterns. These features are useful to distinguish the maximum number of samples accurately and it is matched with already stored image samples for person verification. The simulated results will be shown that used methodologies have better discriminatory power and recognition accuracy compared with prior approaches.? Face detection is a type of biometric software application that can identify a specific individual in a digital image by analyzing and comparing patterns. Facial detection systems are commonly used for security purposes but are increasingly being used in a variety of other applications.
INTRODUCTION
The identification of objects during an image and would altogether probability begin with image methodology techniques like noise removal, followed by (low-level) feature extraction to hunt outlines, regions, and probably unit-like positive textures. One reason typically beans flinch is that degree objects will seem terribly altogether distinction once viewed from wholly altogether totally different completely different angles or at a lower place different lighting. an image might be a few of your time taken as a two-dimensional array of brightness values and is most familiarly pictured by such patterns as those of pictures, sliders, diode LCD TV screen, or show screen. Here we are going to count the persons present in front of the camera. This is done by using the Haar cascade algorithm, such a powerful one to detect a face and counting purpose. By using this and some other image processing techniques we are going to count the persons.
EXISTING SYSTEMS
- Appearance-based methods involve LDA
- Geometric methods.
DISADVANTAGES
- In appearance-based methods, less accurate features description because of whole image consideration
- In geometric based methods, geometric features like the distance between eyes, face length, width, etc., are considered which do not provide optimal results
- More time consumption
- The accuracy of output is less
PROPOSED SYSTEM
- Feature extraction
- HAAR cascade algorithm
ADVANTAGES
- Detection is attained accurately
- Less time consumption
- Accuracy of output is increased
BLOCK DIAGRAM
HARDWARE BLOCK DIAGRAM
CIRCUIT DIAGRAM
HARDWARE REQUIREMENTS
- Raspberry pi
- Camera
SOFTWARE REQUIREMENTS
- Raspberry pi OS
- Python IDE
- OpenCV library
REFERENCES
- Ahonen.T, Hadid.A and Pietik? inen.M, (2004)?Face description with local binary patterns?, in Proc. Eur. Conf. Comput. Vis.
- Anbang Yao and Shan Yu, (2013) ?Robust Face Representation Using Hybrid Spatial Feature Interdependence Matrix?.
- Daubechies. I, (1990)? The wavelet transform time-frequency localization and signal analysis?, IEEE Trans. Information Theory.
- Jain.A.K,(1989) ?Fundamentals of digital image processing?, Prentice-Hall.
- JulienMeynet,(16th July 2003)?Fast Face Detection Using AdaBoost?.
- Moghaddam.B, Wahid.W and Pentland.A,(1998) ?Beyond eigenfaces: Probabilistic matching for face recognition?, Proceeding of face and gesture recognition.
- Noha E. El-Sayad, Rabab Farouk Abdel-Kader, Mahmoud Ibraheem Marie,(2013)? Face? Recognition? as? an? Authentication? Technique? in? Electronic Voting?.
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