Intelligent Broken Image Restorer Test phase, srs, design phase and source code final deliverable

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Intelligent Broken Image Restorer Test phase, srs, design phase and source code final deliverable

Programming

/ Introduction

Old pictures evoke a sense of sentimentality, remind us of a good time gone by and bring back the memories of friends, family, places and events. They are a window to the past that can help us to connect ourselves with our history and use them as a tool to preserve our memories. With the passage of time old pictures get damaged and damaged pictures may lose some information or a portion of our good memory. Restoring damaged or broken images can help to preserve their historical or sentimental value. This is particularly important for images that are rare, irreplaceable, or have significant cultural or historical significance.AI (Artificial Intelligence) can be used to restore the broken images to bring back the complete memory related to broken images.

Functional Requirements:

You are required to develop an AI based web application which can restore a broken image. The details of some functional requirements of broken image restoration application are given below.

1. The application should be able to restore the scanned broken images provided in the formats such as JPEG, PNG, etc. as well as different colour modes like greyscale (black and white), RGB (colourful).
2. The application should be good enough to detect and repair common image defects such as scratches, noise, missing pixels, and other distortions.
3. The friendly user interface of the application should have clear navigation options and straightforward controls that enable the user to select, preview, and restore the image.
4. There should be options to restore a single image or a batch (multiple) of images.
5. The application should have some additional image enhancement options like brightness, contrast, saturation, and sharpness adjustments, which can be used to further improve the restored image.
6. Application should show the comparison of original and restored image. After looking at the preview of the restored image user can make further enhancements in the image before saving (downloaded) the image.

Following are the some examples of restored broken images.

Tools:

PHP (SimpleImage)

ASP.Net (FreeImage, DotImage) Python (OpenCV, Scikit-image, ImageIO, Numpy)

Supervisor:

Name: Muhammad Ahmad Lodhi