We propose a method for synthetic zooming of tomographic images by applying super resolution technique on reconstructed data via a union of rotated lattices.

Download here

Robust matching of multi-modal retinal images using radon transform based local descriptor

Published in IHI 10: Proceedings of the 1st ACM International Health Informatics Symposium, 2010

A novel Radon Transform based descriptor is proposed, which is invariant to illumination, rotation and partially to scale.

Download here

Local descriptor based on texture of projections

Published in ICVGIP:Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing, 2010

In this paper we propose a novel descriptor that better captures shape information by analysing texture of the radon transform

Download here

Detection and discrimination of disease-related abnormalities based on learning normal cases

Published in Pattern Recognition, 2012

In this paper, we observe the key challenges for representation and feature extraction schemes to be met for detection of abnormalities by learning normal cases.

Download here

Decoding MT motion response for optical flow estimation: An experimental evaluation

Published in 23rd European Signal Processing Conference (EUSIPCO), 2015

Decoding the motion energies is of natural interest for developing biologically inspired computer vision algorithms for dense optical flow estimation. Here, we address this problem by evaluating four strategies for motion decoding: intersection of constraints, linear decoding through learned weights on MT responses, maximum likelihood and regression with neural network using multi scale-features.

Download here

What can we expect from a V1-MT feedforward architecture for optical flow estimation?

Published in Signal Processing: Image Communication, 2015

We show how a V1-MT neural model can be adapted to handle real sequences.

Download here

Bio-inspired computer vision: Towards a synergistic approach of artificial and biological vision

Published in Computer Vision and Image Understanding, 2016

This review paper explores the mutual benefits of cognitive and computer vision

Download here

Recurrent network dynamics reconciles visual motion segmentation and integration.

Published in Scientific Reports, 2017

This paper characterizes the complex spatio-temporal dynamics of MT neurons

Download here

Towards inferring cognitive state changes from pupil size variations in real world conditions

Published in ETRA: Eye Tracking Research and Applications, 2020

In this paper we study how far we are from estimating cognitive state changes from eye movements in real world environments using a variety of visual search tasks

Download here