A Novel Edge Detection Operator for Identifying Buildings in Augmented Reality Applications

TL;DR

This paper introduces a new edge detection operator tailored for improved building feature extraction in augmented reality, emphasizing vertical and horizontal edges to enhance accuracy in identifying building contours.

Contribution

The paper presents a novel edge detection filter that emphasizes vertical and horizontal edges, improving building feature extraction in AR applications.

Findings

Enhanced detection of building contours in AR environments.

Better extraction of facade features using the proposed filter.

Improved accuracy in building identification for AR systems.

Abstract

Augmented Reality is an environment-enhancing technology, widely applied in many domains, such as tourism and culture. One of the major challenges in this field is precise detection and extraction of building information through Computer Vision techniques. Edge detection is one of the building blocks operations for many feature extraction solutions in Computer Vision. AR systems use edge detection for building extraction or for extraction of facade details from buildings. In this paper, we propose a novel filter operator for edge detection that aims to extract building contours or facade features better. The proposed filter gives more weight for finding vertical and horizontal edges that is an important feature for our aim.