Development of a Machine Vision System for Image Recognition of Design Estimates

Abstract

This paper discusses implementation of a machine vision system for pattern recognition of design estimates. The main problem in the development of these systems is the choice of unique features that remain invariant to various kinds of transformations. Angular descriptors were chosen as a dominant feature. The paper presents a comparative analysis of the corner detection methods of the Moravec algorithm, the Harris algorithm, and the Shi–Tomasi algorithm. The authors have developed software in Python language that implements the operation of the Harris detector and the Shih-Tomasi detector. The recognition system is being tested for building 3D models in Blender.