Primates Visual Cortex Inspired Novel Edge Detection Method Satyabrat Malla Bujar Baruah, Uddipan Hazarika, Biswajit Das, and Soumik Roy Abstract Edge detection is one of the basic operations performed in the striate cortex of the primate visual cortex. In order to investigate the process of edge detection and directional feature extraction, detailed morphology of direction-selective ganglion cell (DSGC) has been designed incorporating electrophysiological, physicochemical and structural attributes of a neuron and implemented in a spiking neural network to replicate the behavior of DSGC layer in striate cortex. Simulation results successfully replicate the behavior of DSGC and suggest edge detection as early operation in the primate visual cortex. Results suggest non-maxima suppression as an inherent feature of such networks and edge reconstruction might be achieved due to max-pooling like operation in a single-cell neighborhood with four DSGC depth response. Keywords Direction-selective ganglion cell · Spiking neuron · Visual cortex · Edge detection · DSGC 1 Introduction Primate vision and its role in feature extraction from natural images are some of the aspects yet to be realized in neuronal networks and systems. At the base of such complex biological system [20] resides numerous neurons organized with single-cell precision in multiple layers [18, 26] that performs complex feature extraction with high speed, accuracy at ease. Very little is known about the underlying processes involved in achieving such accurate and robust features. Several spiking neural net- works (SNN) [7, 27, 29] are designed and simulated incorporating unique linear and nonlinear activation functions based on biologically plausible neuronal attributes to understand the underlying dynamics of such robust networks. One of such bio- logically inspired network is Poggio’s hmax model [21–23] that tries to replicate S. M. B. Baruah · U. Hazarika (B ) · B. Das · S. Roy Department of Electronics and Communication Engineering, Tezpur University, Napam, Sonitpur, Tezpur, Assam 784028, India e-mail: xoumik@tezu.ernet.in © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 T. K. Gandhi et al. (eds.), Advanced Computational Paradigms and Hybrid Intelligent Computing, Advances in Intelligent Systems and Computing 1373, https://doi.org/10.1007/978-981-16-4369-9_35 357