Canny and Morphological Approaches to Calculating Area and Perimeter of Two-Dimensional Geometry

Abstract

Calculating area and perimeter in real-world conditions has its challenges. The actual conditions include applications in the medical field to measure the presence of tumors or the condition of human organs and applications in geography to measure specific areas on a map; applications in architecture often calculate the area and perimeter of buildings, interior design, exterior design, and other uses. Technology can make it easier with automatic calculations. Mathematical methods and computer vision techniques are required to create automated systems. The Canny method is usually used, which is good enough for detecting edges but not sufficient for measuring irregular geometric shapes. This paper aims to calculate the area and perimeter of a geometric shape using the Canny method and geometry. Data samples in various forms are used in this study. Calculating area and perimeter using the Canny method involves obtaining the length (X,Y) of the RGB image converted to HSV. Edge detection values are used to calculate the area and perimeter of objects. The morphological method uses binary image input as input data. Then proceed to the convolution process with structuring and calculating the area and circumference of objects. Based on the research results, calculating the area and circumference of objects is more effective using morphological methods. However, the level of accuracy is affected by the selection of structuring elements (strels) which must be optimal and global.