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  Published Paper Details:

  Paper Title

Augmenting of Corrupted Image from CCTV footage

  Authors

  Dr.K.Geetha,  R.Ragavi,  M.Shanmuga Priya,  K.Swetha

  Keywords

SRGAN, Image Enhancement, surveillance system, noise reduction, Super Resolution, Upsampling, Batch Normalisation, Peak Signal to Noise Ratio (PSNR).

  Abstract


Recently, image recognition technology using deep learning has improved significantly. Forensic analysis has proved to be one of the most utilitarian tool in investigating crime. Forensic analysis provides evidence / basic information of the said crime through analysis of physical evidence. This project address a scintillating technique to enhance the image quality of CCTV video to assist in the investigation of criminal cases. In the pre- processing phase for face recognition, face data with seven features that can be identified as a person are collected using CCTV. The collected dataset goes through the annotation process to classify the data and facial features are detected using deep learning. If there are four or more detected features, the image data is determined to be a person and the face is matched with stored user data in detail using 81 feature vectors. The problem of enhancing images is addressed by pure image processing method and machine learning technique. This project analyzes both of the above techniques and further concluded that the machine learning approach produces a more efficient result. The application of this technique can range from simple image filtering and advanced forensic image processing.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2305652

  Paper ID - 236972

  Page Number(s) - f424-f430

  Pubished in - Volume 11 | Issue 5 | May 2023

  DOI (Digital Object Identifier) -    http://doi.one/10.1729/Journal.34277

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Dr.K.Geetha,  R.Ragavi,  M.Shanmuga Priya,  K.Swetha,   "Augmenting of Corrupted Image from CCTV footage", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 5, pp.f424-f430, May 2023, Available at :http://www.ijcrt.org/papers/IJCRT2305652.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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