Print Data Matrix Barcode using Python
Title: - A Watermarking Technique to Secure Printed Matrix Barcode—Application for Anti-Counterfeit Packaging
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Implementation Plan:
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Step 1: Initially, we load the original digital images and select the input image.
Step 2: Next we perform the CLIPPING GAUSSIAN NOISE TEXTURE process, In this process the CGN texture is created from an input image of a 2D random Gaussian signal by replacing all values.
Step 3: Next MAGE TEXTURE IDENTIFICATION SOLUTION, In this step we add some white noise using a dithering algorithm. After adding some white noise, the image passes through a Gaussian filter to be blurred.
Step 4: Next we perform the image noise and it is extracted and embedded into the image after that. Finally, the image is scaled down by 1/2 to obtain the final simulated printed image.
Step 5: Next, we perform CLASSIFICATION OF SIMULATED IMAGES, In this process based on the extracted features we classified the image as Numerical, Genuine and Falsified.
Step 6: Finally, we validate the performance of these work,
• Number of images vs. Accuracy
• Number of images vs. Recall
• Number of images vs. Precision
• Number of images vs. F-Score
• ROC Curve
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Software Requirement:
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Language : Python
IDE : Python-3.10.4
Operating System : Windows-10 (64-bit)
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