Security alert by face recognition using gabor wavelet algorithm
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Security alert by face recognition using gabor wavelet algorithm

Project period

06/29/2017 - 07/29/2017

Views

267

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Security alert by face recognition using gabor wavelet algorithm
Security alert by face recognition using gabor wavelet algorithm

This project deals that the faces are compared from the streaming video with the database images. The input streaming video is first converted into the frame by frame images and then these images are compared with the database image. Thus this comparison is done with the help of Gabor Wavelet Algorithm. If both the images are matched then the location of which the camera the images are captured can be determined easily and the time at which the image is captured can also be determined by interfacing the cameras. Further SMS can also be sent to the authorized persons if needed.

This project introduces the well-known Gabor wavelet transform and its application. The multi-resolution and multi-orientation properties of the Gabor wavelet transform makes it a popular method for feature extraction even if the intrinsic no orthogonality exists. Among all the works based on Gabor wavelet, face recognition and texture representation are the most noticeable applications, and other researchers used the Gabor wavelets mainly for feature extraction. Several Matlab implementations are presented in this report and show both the theoretical and application aspects of Gabor wavelets. There seems no further necessity to modify the formula of Gabor wavelets while the feature representation and the possible applications remain spaces for future work.

Why: Problem statement

Here, we discuss the security problems. Security is the major issue in some of the sectors like access to limited areas, banking identity confirmation and identification of wanted people at airports. This project plans to reduce those issues. By identifying the face using cameras and alert will be given to authorized persons when needs. Face recognition will be done with the help of Gabor Wavelet Algorithm which has an advantage of 4D recognition and high energized point comparison. It also improves the quality of the captured image. Faces are captures from the streaming video. Faces compare between a captured image with the database of image and alert through GSM module.

How: Solution description

By recognizing the face we can increase the security issues. This project report introduces the well-known Gabor wavelet transform and its application. The multi-resolution and multi-orientation properties of the Gabor wavelet transform makes it a popular method for feature extraction even if the intrinsic nonorthogonality exists. Among all the works based on Gabor wavelet, face recognition and texture representation are the most noticeable applications, and other researchers used the Gabor wavelets mainly for feature extraction. Several Matlab implementations are presented in this project and show both the theoretical and application aspects of Gabor wavelets. There seems no further necessity to modify the formula of Gabor wavelets while the feature representation possible applications remain spaces for future work.

How is it different from competition

The image is given as input. The image is compared to the input video and the face is recognized and the output is displayed.

 If both the images are matched then the location of which the camera the images are captured can be determined easily and the time at which the image is captured can also be determined by interfacing the cameras. Further SMS can also be sent to authorized persons if needed.

From the input video, the face is recognized and the face is matched. The face is compared with the video in the frame by frame manner and the output is displayed. The output is displayed.

Who are your customers

This project deals that the faces are compared from the streaming video with the database images. The input streaming video is first converted into the frame by frame images and then these images are compared with the database image. Thus this comparison is done with the help of the Gabor Wavelet Algorithm.

If both the images are matched then the location of which the camera the images are captured can be determined easily and the time at which the image is captured can also be determined by interfacing the cameras. Further SMS can also be sent to authorized persons if needed.

Project Phases and Schedule

Phase 1: Data Collection.

Phase 2: Data Analysis.

Phase 3: Prediction.

Resources Required

Tool required: Anaconda - Python 3.6 version

Jupyter notebook

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