The project is based on multiple face detection using the Haar cascade algorithm. The proposed system involves multiple face detection and Features extraction. Multiple Face detection is to detect faces based on a haar cascade algorithm using python toolbox.? In the feature extraction stage, the GLCM is used for different object texture and edge contour feature extraction process. 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. Multiple 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.
The identification of objects during an image and this would altogether probability begin with image methodology techniques like noise removal, followed by (low-level) feature extraction to hunt out lines, 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 a 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.
- Appearance based methods involves LDA
- Geometric methods.
- In appearance based methods, less accurate of features description because of whole image consideration
- In geometric based methods, the geometric features like distance between eyes, face length and width, etc., are considered which not provides optimal results
- More time consumption
- Accuracy of output is less
- Feature extraction
- HAAR cascade algorithm
- Detection is attained accurately
- Less time consumption
- Accuracy of output is increased
HARDWARE BLOCK DIAGRAM
- Raspberry pi
- Raspberry pi OS
- Python IDE
- OpenCV library
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