• V. Nisha Malar
• Ms.K. Saranya
• V. Raamaanujam
• T.S Thev Harsil

The project aims to classify various colour through visually evoked stimulations in brain responsible for perceiving and understanding the sense of various colour. This is achieved in two main steps. First step, we record the brain signals using Electroencephalography response to different colour stimuli from the scalp using the standard 8 electrode system. Experiments undertaken using G-Nautilus software reveal that there exists long term (around 1 second) correlations between activated brain regions and the perceptual process of specific colour stimulus. For instance, the parietal and the occipital lobe activations have long duration correlations with the blue colour stimuli; whereas the prefrontal and the occipital lobe activations have correlations with the red colour, while the temporal and the occipital lobe activations have correlations with the green colour. In the second step, we classify the perceived colour of the brain signals acquired from the selected brain regions. A feed forward Neural Network with back propagation classifier has been designed to perform the classification process by utilizing the brain signals from the activated lobes. Performance analysis followed by statistical tests undertaken reveals that the Neural Network classifier outperforms its traditional counterparts by a wide margin. The proposed technique is expected to have interesting applications to explain the malfunctioning in recognition of coloured stimuli due to damage in certain brain lobes like occipital, temporal etc.

"CLASSIFICATION OF VISUALLY EVOKED POTENTIAL FOR COLOR PERCEPTION USING SOFT COMPUTING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.i152-i164, May-2022, Available :http://www.jetir.org/papers/JETIR2205921.pdf

"CLASSIFICATION OF VISUALLY EVOKED POTENTIAL FOR COLOR PERCEPTION USING SOFT COMPUTING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppi152-i164, May-2022, Available at : http://www.jetir.org/papers/JETIR2205921.pdf