International Journal of Electrical and Electronics Research (IJEER) Open Access | Rapid and quality publishing Research Article | Volume 10, Issue 4 | Pages 1036-1042 | e-ISSN: 2347-470X 1036 Website: www.ijeer.forexjournal.co.in A Novel Hexagonal Psuedo framework for Edge Detection Operators on Hexagonal Framework ░ ABSTRACT- Edge detection using a gradient-based detector is a gold-standard method for identifying and analyzing different edge points in an image. A hexagonal grid structure is a powerful architecture dominant for intelligent human-computer vision. This structure provides the best angle resolution, good packing density, high sampling efficiency, equidistant pixels, and consistent connectivity. Edge detection application on hexagonal framework provides more accurate and efficient computations. All the real-time hardware devices available capture and display images in rectangular-shaped pixels. So, an alternative approach to mimic hexagonal pixels using software approaches is modeled in this paper. In this research work, an innovative method to create a pseudo hexagonal lattice has been simulated and the performance is compared with various edge detection operators on the hexagonal framework by comparing the quantitative and qualitative metrics of the grayscale image in both square and hexagonal lattice. The quantitative performance of the edge detection on the hexagonal framework is compared based on the experimental facts. The pseudo-hexagonal lattice structure assures to be aligned toward the human vision. Keywords: Edge detection operators, Resampling, Spiral addressing architecture, Sampling efficiency, Grayscale image. ░ 1. INTRODUCTION This study discusses hexagonal image processing, a less-known sophisticated image processing approach. Despite the fact that this field of study has been explored for the past 40 years, most of the imaging systems currently in use utilize square lattice rather than hexagonal owing to how simple it is to construct. The hexagonal lattice is the best sampling strategy for circularly band-limited digital signals, providing 13.4% fewer samples than the square lattice, according to the multidimensional sampling theory [1]. In terms of geometric qualities, such as a higher level of symmetry, equal spacing, and uniform connectivity with its six-neighbours, the hexagonal lattice is indeed preferable to ordinary square lattice [2]. There is a need for innovative techniques to acquire hexagonal images in order to get over these fundamental restrictions in square lattice systems. Hexagonal structures are inspired by nature, which accomplishes this in various ways. Since hexagonal pixels closely resemble the form of the human fovea, there is a strong correlation between hexagonal systems and human sensory systems. And, here is the basic explanation of how the human eye captures images to help make the link. The retina is a delicate membrane located inside the back of the eye. The retina's goal is to collect light information, which the brain then translates into neural impulses for visual identification. The fovea is a tiny region of the retina. The fovea's structural design is hexagonally positioned and has a highly dense conical shape, which acquires clearer vision than a square grating arrangement. As per [3], [4], [5], [6], the structure of the hexagonal lattice offers an additional advantage over the square lattice when detecting straight and circular edges, which provides a higher accuracy [6]. This results in greatly improved precision of circular and near-circular images when processed [7]. Another key factor in this digital imaging technology is spatial sampling efficiency. The spatial sampling efficiency by the hexagonal structure is superior over a rectangular grid of similar pixel separation, which reflect better computation and fewer (13% less) pixel requirement to achieve the same image resolution when compared to a rectangular grid. Fadaei & Rashno [8] proposed an efficient simulation approach for converting square to hexagonal lattices. Xiangguo Li [9] also proposed a hexagonal lattice conversion algorithm using a 1-D interpolation kernel rather than a 2-D interpolation kernel. Edge detection and image enhancement are the two areas in which computer vision concepts expand and will require increasing demand to know the structure of the irregular curves contained in that image. Consequently, it is of vital significance resulting in dissimilar methods for identifying the structure of A Novel Hexagonal Psuedo framework for Edge Detection Operators on Hexagonal Framework Prathibha Varghese 1 and Dr. G. Arockia Selva Saroja 2 1 Research Scholar, Department of Electronics and Communication Engineering, Noorul Islam Centre for Higher Education, Thuckalay, Kumaracoil-629180, Tamil Nadu, India, prathibhavarghese2003@gmail.com 2 Associate Professor, Department of Electronics and Communication Engineering, Noorul Islam Centre for Higher Education, Thuckalay, Kumaracoil-629180, Tamil Nadu, India, arockiaselvasaroja@niuniv.com *Correspondence: Prathibha Varghese: prathibhavarghese2003@gmail.com ARTICLE INFORMATION Author(s): Prathibha Varghese and Dr.G. Arockia Selva Saroja; Received: 21/08/2022; Accepted: 24/10/2022; Published: 20/11/2022; E- ISSN: 2347-470X Paper Id: IJEER 22701 Citation: 10.37391/ijeer.100446 Webpage-link: https://ijeer.forexjournal.co.in/archive/volume-10/ijeer-100446.html Publisher’s Note: FOREX Publication stays neutral with regard to jurisdictional claims in Published maps and institutional affiliations.