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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
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Published Paper Details:
Authors
Sakshi Kale,Piyush Patil,Muskan Mulla,Sakshi Panmand,Manisha Desai
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Keywords
Computer Vision, Machine Learning, DeepLearning.
Abstract
Innovative research attempts have been spurred by the constant difficulty of shadows affecting image quality in the field of
computer vision and image processing. This research explores the creation of a reliable and effective shadow removal system
using state-of-the-art image processing methods. Shadows reduce image clarity and interfere with visual perception, frequently
serving as obstacles in a variety of applications. This research attempts to tackle this problem from all angles in order to
revolutionize image processing. Naturally occurring in images are shadows cast by obstructing light sources, which cause colour
distortion and decreased visibility. Shadows impede precise object identification and scene comprehension in computer vision.
The limits of traditional shadow removal technologies require the investigation of more sophisticated strategies in order to
address these issues. The common appearance of shadows in images, which restricts applications like automated surveillance,
object detection, and medical imaging, is the driving force behind this research. Eliminating shadows improves automated
systems' accuracy and dependability in addition to their visual appeal. This work has broad implications for many domains
where accurate image processing is critical. The creation of a novel shadow removal system that can precisely detect and remove
shadows from photos is the main result of this research. The suggested method ensures accurate removal without sacrificing
image integrity by using advanced algorithms and machine learning models to discern between shadows and real objects. After
a great deal of testing and verification, the system performs exceptionally well in a range of lighting scenarios with complicated
shadows. By combining powerful image processing algorithms with machine learning approaches, this study presents a
revolutionary methodology. The system's capacity to adaptively learn and distinguish shadows from other picture elements,
guaranteeing great accuracy and efficiency, is what makes it innovative. Furthermore, the addition of real-time processing
capabilities represents a significant development and enables the system to be used in time-sensitive applications. In conclusion,
this study not only tackles the ubiquitous problem of shadows in photos but also makes a significant contribution to the field of
image processing. The system that was created is evidence of the collaboration between state-of-the-art algorithms and
creative approaches, opening the door to improved image quality and the development of computer vision applications.
IJCRT's Publication Details
Unique Identification Number - IJCRT2312311
Paper ID - 247812
Author type - Indian Author
Page Number(s) - c737-c744
Pubished in - Volume 11 | Issue 12 | December 2023
DOI (Digital Object Identifier) -
No Of Downloads - 45
Author Country - India, 411058, Pune, Pune, 411058, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Published Paper PDF : - http://www.ijcrt.org/papers/IJCRT2312311
Published Paper URL: : - http://ijcrt.org/viewfull.php?&p_id=IJCRT2312311
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Sakshi Kale,Piyush Patil,Muskan Mulla,Sakshi Panmand,Manisha Desai, "Single Image Shadow Removal Using Deep Learning", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 12, pp.c737-c744, December 2023, Available at :http://www.ijcrt.org/papers/IJCRT2312311.pdf
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The International Journal of Creative Research Thoughts (IJCRT) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies.
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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