论文标题
根据角落检测，自主删除电梯按钮图像的透视扭曲
Autonomous Removal of Perspective Distortion of Elevator Button Images based on Corner Detection
论文作者
论文摘要
电梯按钮识别是实现电梯自主操作的关键功能。但是，具有挑战性的图像条件和各种图像扭曲使得难以准确识别按钮。为了填补这一空白，我们提出了一种新颖的基于深度学习的方法，该方法旨在根据按钮角检测结果自主纠正电梯按钮图像的视角扭曲。首先，我们利用一种新型的图像分割模型和Hough变换方法来获得按钮分割和按钮转角检测结果。然后，将标准按钮角的像素坐标用作参考功能，以估算校正透视扭曲的相机运动。 15个电梯按钮图像是从不同角度作为数据集捕获的。实验结果表明，我们提出的方法能够估计摄像头动作并以高精度消除电梯按钮图像的透视扭曲。
Elevator button recognition is a critical function to realize the autonomous operation of elevators. However, challenging image conditions and various image distortions make it difficult to recognize buttons accurately. To fill this gap, we propose a novel deep learning-based approach, which aims to autonomously correct perspective distortions of elevator button images based on button corner detection results. First, we leverage a novel image segmentation model and the Hough Transform method to obtain button segmentation and button corner detection results. Then, pixel coordinates of standard button corners are used as reference features to estimate camera motions for correcting perspective distortions. Fifteen elevator button images are captured from different angles of view as the dataset. The experimental results demonstrate that our proposed approach is capable of estimating camera motions and removing perspective distortions of elevator button images with high accuracy.
