Project Description » History » Revision 17
Revision 16 (Joseph Eugene PELC, 10/24/2024 01:54 PM) → Revision 17/74 (MYAT Ma De May Phuu Ngon, 10/24/2024 02:12 PM)
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*[[/|Home]]* | *[[Team Members]]* | *[[Project Description]]* | *[[Code]]* | *[[UML Diagrams]]* | *[[Results]]* |
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h1=. <pre>
Project Description </pre>
*Overview*
The aim of this project is to output two different projector images merged into one singular display. We used techniques such as gamma correction, alpha blending, and modification of intensities on the images, in order to get the final result. Our project will have a project manager, team leader, Doxygen documentation team, wiki team, coding team, and UML design team.
*Software and Tools*
%{color: red}Redmine% - We used Redmine to track our progress and tasks we need to finish
%{color: green}Python / OpenCV% - For image processing we used OpenCV within Python
%{color: blue}Doxygen% - We used Doxygen for the code documentation
%{color: purple}Astah% - To create UML diagrams of the code
*Technology*
*Alpha Blending Method*
The code defines an image processing application using Tkinter for the GUI, OpenCV for image manipulation, and PIL for rendering. It allows users to load configuration files, process images with gamma correction and alpha blending, and display or save the results.
*Gamma Correction Method*
*Key Features*
ConfigReader reads settings like image path, blending width, gamma value, and transparency from a config file.
This project incorporates a method called MaskCreator applies gamma correction which adjusts the to adjust brightness of an and alpha blending to create smooth transitions on image by altering its luminance values to each value of the pixel in edges (left or right).
ImageProcessingApp provides a non-linear manner. This is helpful in matching to human perception of light. Compared to a camera, we are much more sensitive to changes in dark tones than we are to similar changes in bright tones. There's a biological reason simple interface for this peculiarity: it enables our vision to operate over selecting config files, processing images, and displaying results with a broader range of luminance.
Gamma correction involves applying a power-law function to the pixel values of an image. progress bar.
The formula used is
V out =V in^γ
where Vin is the input pixel value, and γ is the gamma value.
If the gamma is greater than 1, the image becomes darker; if it's less than 1, the image appears brighter.
*gamma_corrected = (image / 255.0)^gamma * 255*
Note: Gamma is the provided gamma value. Since pixel values range from 0 to 255, the original image is first normalized (divided alpha blending technique merges images by 255), then raised to gradually transitioning the power of gamma, and finally rescaled to the 0-255 range.
!before_gamma.jpg!
*Before Gamma Correction*
!after_gamma.jpg!
*After Gamma Correction*
Note: gamma is the provided gamma value. Since pixel values range from 0 to 255, the original image is first normalized (divided by 255), then raised to the power of gamma, and finally rescaled to the 0-255 range. edges, creating smooth, seamless composites.