Ashutosh Aggarwal
Lecturer

Designation:

Lecturer

Specialization:

Image and Video Processing

Email:

ashutosh.aggarwal@thapar.edu

Contact No.

+91-9988-099-471

Biography :

Ashutosh Aggarwal is currently working as Lecturer in the Department of Computer Science and Engineering, Thapar Institute of Engineering & Technology, Patiala, Punjab, India. He received his B.Tech. and M.Tech. degrees in Computer Science and Engineering from Guru Nanak Dev University, Amritsar, India and B.R. Ambedkar National Institute of Technology, Jalandhar, India in 2010 and 2012, respectively. He is currently pursuing Ph.D. in Computer Science from Punjabi University, Patiala, India. His current research interests include Image Super-Resolution, Image and Video Denoising, Face Recognition, Image Retrieval, Pattern Recognition, Optical Character Recognition, etc.

Research Projects

Membership of Professional Institutions, Associations, Societies

ISTE Life Time Membership

Publications and other Research Outputs

SCI

  1. 1. Chandan Singh, Ashutosh Aggarwal, An Efficient and Robust Multi-Frame Image Super-Resolution Reconstruction Using Orthogonal Fourier-Mellin Moments, Displays 49 (2017): 101-115.
  2. Chandan Singh, Ashutosh Aggarwal, Single-image super-resolution using orthogonal rotation invariant moments, Computers & Electrical Engineering (2017) doi: http://dx.doi.org/10.1016/j.compeleceng.2017.02.009.
  3. Chandan Singh, Ashutosh Aggarwal, Sukhjeet K. Ranade, A new convolution model for the fast computation of Zernike moments, International Journal of Electronics and Communications (AEÜ), 72(2017): 104-113.
  4. Ashutosh Aggarwal, Chandan Singh, Zernike Moments based Gurumukhi Character Recognition, Applied Artificial Intelligence 30 (2016): 429-444.
  5. Chandan Singh, Ashutosh Aggarwal, A Comparative Performance Analysis of DCT-Based and Zernike Moments-Based Image Up-Sampling Techniques, Optik 127 (2016): 2158-2164.
  6. Chandan Singh, Ashutosh Aggarwal, An Efficient Approach for Image Sequence Denoising Using Zernike Moments-Based Nonlocal Means Approach, Computers & Electrical Engineering (2015) doi: http://dx.doi.org/10.1016/j.compeleceng.2015.09.006.
  7. Chandan Singh, Ashutosh Aggarwal, A Noise Resistant Image Matching Method Using Angular Radial Transform, Digital Signal Processing 33 (2014): 116-124.

Non-SCI

  1. Ashutosh Aggarwal, Karamjeet Singh, Kamalpreet Singh, Use of Gradient Technique for extracting features from Handwritten Gurmukhi Characters and Numerals, Procedia Computer Science 46 (2015): 1716-1723.
  2. Ashutosh Aggarwal, Rajneesh Rani, Renu Dhir, Recognition of Devanagari Handwritten Numerals using Gradient Features and SVM, International Journal of Computer Applications 48 (2012): 39-44.
  3. Ashutosh Aggarwal, Sukhpreet Singh, Offline Handwritten Gurmukhi Numeral Recognition Using SVM and Different Feature Sets, International Journal of Advanced Research in Computer Science 3 (2012): 379-383.
  4. Ashutosh Aggarwal, Rajneesh Rani, Renu Dhir, Handwritten Devanagari Character Recognition using Gradient Features, International Journal of Advance Research in Computer Science and Software Engineering 2 (2012): 85-90.
  5. Sukhpreet Singh, Ashutosh Aggarwal, Renu Dhir, Use of Gabor Filters for recognition of Handwritten Gurmukhi Characters, International Journal of Advance Research in Computer Science and Software Engineering 2 (2012): 234-240.

International Conferences

  1. Ashutosh Aggarwal, Chandan Singh, Hybrid DCT-Zernike Moments-Based Approach for Image Up-Sampling, in Proceedings of 12th Annual IEEE India Conference 2015 (INDICON), IEEE. DOI: 10.1109/INDICON.2015.7443143.
  2. Ashutosh Aggarwal, Karamjeet Singh, Zernike Moments-Based Retrieval of CT and MR Images, in Proceedings of 12th Annual IEEE India Conference 2015 (INDICON), IEEE. DOI: 10.1109/INDICON.2015.7443132.
  3. Ashutosh Aggarwal, Karamjeet Singh, Handwritten Gurmukhi Character Recognition, in Proceedings of 2015 IEEE International Conference on Computer Communication and Control (IC4-2015), IEEE. DOI: 10.1109/IC4.2015.7375678

Research Experience

  1. Project Fellow, in UGC SAP (DRS-II) sponsored project in the Dept. of Computer Science, Punjabi University, Patiala from 7th December 2012 to 31st March 2014.
  2. Project Fellow, in UGC SAP (DRS-III) sponsored project in the Dept. of Computer Science, Punjabi University, Patiala from 25th August 2015 to 28th June 2016.

Awards and Honours

  • Qualified GATE (CS) 2010 with 98 percentile.
  • Qualified GATE (CS) 2013 with 97 percentile.
  • Qualified UGC NET December 2012.
  • Organized Two-Week MHRD sponsored ISTE workshop conducted by IIT BOMBAY in NIT Jalandhar

Description of Research Interests

Ashutosh Aggarwal’s research interests are in single-image super-resolution as well as super-resolution of input video sequences. His interest lies in exploring the use of orthogonal rotation invariant moments (ORIMs) for image super-resolution application, because of their superior reconstruction ability and high robustness towards noise. Besides this, he is currently working on the efficient and effective retrieval of bio-medical images such as MRI and CT, using ORIMs and local feature descriptors based on LBP.