An X-ray Image Enhancement Algorithm for Dangerous Goods in Airport Security Inspection
Objective
Study the problem of "airport security X-ray image enhancement", and proposes an image enhancement algorithm of USM+CLAHE.
Abstract
An X-ray image enhancement technique integrating USM+CLAHE is presented to address the problem of colour distortion in CLAHE enhanced airport security X-ray images. Calculating the grayscale images on the R, G, and B channels of the X-ray image and applying CLAHE enhancement to each, then merging the enhanced R, G, and B grayscale images will take place.
After that, USM sharpening operation is applied to the CLAHE-enhanced X-ray image, and then it is merged with the original and USM-sharpened images according to the weight. The results of the experiments reveal that the USM+CLAHE algorithm can successfully improve the security X-ray image while also suppressing colour distortion in the enhanced image.
Keywords: Airport security, X-ray image, USM, CLAHE, Image enhancement
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
- Introduction to Matlab
- What is EISPACK & LINPACK
- How to start with MATLAB
- About Matlab language
- Matlab coding skills
- About tools & libraries
- Application Program Interface in Matlab
- About Matlab desktop
- How to use Matlab editor to create M-Files
- Features of Matlab
- Basics on Matlab
- What is an Image/pixel?
- About image formats
- Introduction to Image Processing
- How digital image is formed
- Importing the image via image acquisition tools
- Analyzing and manipulation of image.
- Phases of image processing:
- Acquisition
- Image enhancement
- Image restoration
- Color image processing
- Image compression
- Morphological processing
- Segmentation etc.,
- About Artificial
Intelligence (AI)
- About Machine
Learning
- About Deep
Learning
- About layers in
AI (input, hidden and output layers)
- Building AI
(ANN/CNN) architecture using Matlab
- We will
able to know, what’s the term “Training” means in Artificial Intelligence
- About requirements that can influence the AI training process:
- Data
- Training data
- Validation data
- Testing data
- Hardware requirements to train network
- How to detect an object using AI
- How to extend our work to another real time applications
- Project development Skills
- Problem analyzing skills
- Problem solving skills
- Creativity and imaginary skills
- Programming skills
- Deployment
- Testing skills
- Debugging skills
- Project presentation skills
- Thesis writing skills
Related Projects
Paper Publishing
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Disclaimer - Takeoff Edu Group Projects, are not associated or affiliated with IEEE, in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, and not projects of or by IEEE.
