Open AccessDoor Detection Based on Geometrical Features and Harris Corner
Author(s) -
Md. Akber Hossain et.al
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i3.1572
Subject(s) - computer science , artificial intelligence , robustness (evolution) , corner detection , computer vision , prewitt operator , edge detection , detector , robot , task (project management) , pattern recognition (psychology) , image (mathematics) , image processing , engineering , telecommunications , biochemistry , chemistry , systems engineering , gene
Door is a very significant element as it enables a person to enter a house or room. Though identifying doorway is an easy task for a regular person, for robots or visually impaired people it is a challenging task. To overcome this challenge, we have proposed a door detection method. Our proposed method is based on Prewitt edge detection method and Harris corner detector. Here, we are using a number of predefined rules to detect the doorframe correctly. To establish the robustness of our proposed method, we have formed a substantial dataset of scene images that are captured in various unfamiliar environments. Our experimental results validate that our proposed method is robust against changes in viewpoint, shapes, occlusions, illumination, colors, sizes, orientations, and textures of the door. The experimental results show that our proposed method reaches 87.45% accuracy as well as achieves lower false positive rate and lower computational time.