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Nature-inspired computing has been a real source of motivation for the development of many meta-heuristic algorithms. The biological optic system can be patterned as a cascade of sub-filters from the photoreceptors over the ganglion cells in the fovea to some simple cells in the visual cortex. This spark has inspired many researchers to examine the biological retina in order to learn more about information processing capabilities. The photoreceptor cones and rods in the human fovea resemble hexagon more than a rectangular structure. However, the hexagonal meshes provide higher packing density, consistent neighborhood connectivity, and better angular correction compared to the rectilinear square mesh. In this paper, a novel 2-D interpolation hexagonal lattice conversion algorithm has been proposed to develop an efficient hexagonal mesh framework for computer vision applications. The proposed algorithm comprises effective pseudo-hexagonal structures which guarantee to keep align with our human visual system. It provides the hexagonal simulated images to visually verify without using any hexagonal capture or display device. The simulation results manifest that the proposed algorithm achieves a higher Peak Signal-to-Noise Ratio of 98.45 and offers a high-resolution image with a lesser mean square error of 0.59.

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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.

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