Binary-Patterns Based Floor Recognition Suitable for Urban Scenes

Osuna-Coutiño, J. A. de Jesús; Martínez-Carranza, José

doi:10.1109/codit.2019.8820296

Cited by 4 publications

(1 citation statement)

References 22 publications

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“…De Jesús Osuna-Coutiño and Martinez-Carranza [13] proposed a combined approach for floor segmentation made two types of analysis. The first one was floor connection, used for increasing recognition robustness.…”

Section: Literature Reviewmentioning

confidence: 99%

Floor Segmentation Approach Using FCM and CNN

Ravishankar¹,

Devaraj²,

Hanumathaiah³

2023

ATAIML

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Floor plans play an essential role in the architecture design and construction, which serves as an important communication tool between engineers, architects and clients. Automatic identification of various design elements in a floor plan image can improve work efficiency and accuracy. This paper proposed a method consists of two stages, Fuzzy C-Means (FCM) segmentation and Convolutional Neural Network (CNN) segmentation. In FCM stage, the given input image was partitioned into homogeneous regions based on similarity for merging. In CNN stage, the interactive information was introduced as markers of the object area and background area, which were input by the users to roughly indicate the position and main features of the object and background. The segmentation evaluation was measured using probabilistic rand index, variation of information, global consistency error, and boundary displacement error. Experiments were conducted on real dataset to evaluate performance of the proposed model. The experimental results revealed the proposed model was successful.

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Section: Literature Reviewmentioning

confidence: 99%