Performance Analysis of Face Recognition on Gabor Wavelet Transform and VGG Convolutional Neural Network
Implementation Plan:
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Step 1: Initially, We load the input images from WiderFace dataset.
Step 2: Next, Perform the Data Preprocessing by this process includes image size normalization and Image deaverage operator.
Step 3: Next, load the preprocessed image and perform the features extraction by using Discrete wavelet transform (DWT) and Roi.
Step 4: Next, we extract the feature vector of the image by the operation of the convolution kernel.
Step 5: Next, perform the Training process by using convolutional neural network (CNN) and light VGG-16 algorithms and detect the face Predict the Boxes by using softmax classifier.
Step 6: Finally, we evaluate the following performance metrics,
6.1: Accuracy
6.2: Precision
6.3: Recall
6.4: F1-Score
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Software Requirement:
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1. Tool: Matlab R2023a
2. OS: Windows 10 – (64-bit)
