Real-Time LCD Digit Recognition System

Saad, Norhashimah Mohd; Noor, N. S. M.; Abdullah, Abdul Rahim; Fong, O. Y.; Rahman, Nor Nabilah Syazana Abdul

doi:10.11591/ijeecs.v6.i2.pp402-411

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…The noise in button areas is filtered, so that there is only the black number on the white background. Now, the seven-segment-like inference mechanism is used to recognize the number inside each area (Saad et al , 2017), as presented in Figure 4(a). A sample rectangle will be located at seven locations { top, top left, top right, center, bottom left, bottom right, bottom } of black number’s contour in the filtered image.…”

Section: Elevator Button Detectionmentioning

confidence: 99%

An efficient approach for the elevator button manipulation using the visual-based self-driving mobile manipulator

Toan

Jeong²,

Jo³

2022

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Purpose Because mobile manipulators are unable to climb stairs, the elevator operation is a crucial capacity to help those kinds of robot systems work in modern multifloor buildings. Here, the elevator button manipulation is considered as an efficient approach to fulfill that requirement. Previously, some studies presented elevator button recognition algorithms while some others designed schemes for the button manipulation work. However, the mobile robot, the manipulator and the camera in their robot systems are asynchronous. Besides, the time-consuming calibration for the camera is inevitable, especially in changeable environments. This paper aims to present an alternative method for the elevator button manipulation to overcome mentioned shortcomings. Design/methodology/approach In this paper, the elevator button manipulation is conducted by using the visual-based self-driving mobile manipulator in which the autonomous mobile robot, the manipulator and the camera cooperate more efficiently. Namely, the mobile robot does not need to be located exactly in front of the elevator panel as the manipulator has the ability to adjust the initial frame of the camera based on the system kinematic synchronization. In addition, the proposed method does not require the real world coordinates of elevator buttons, but uniquely using their pixel positions. By doing this, not only is the projection from two-dimensional pixel coordinates to three-dimensional (3D) real world coordinates unnecessary, but also the calibration of the camera is not required. Findings The proposed method is experimentally verified by using a visual-based self-driving mobile manipulator. This robotic system is the integration of an autonomous mobile robot, a manipulator and a camera mounted on the end-effector of the manipulator. Research limitations/implications Because the surface of the elevator button panel is usually mirror-like, the elevator button detection is easily affected by the glare and the brightness of the environmental light condition. Practical implications This robot system can be used for the goods delivery or the patrol in modern multifloor buildings. Originality/value This paper includes three new features: simultaneously detecting and manipulating elevator buttons without the projection from pixel coordinates to 3D real world coordinates, a kinematic synchronization to help the robot system eliminate accumulated errors and a safe human-like elevator button manipulation.

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Section: Elevator Button Detectionmentioning

confidence: 99%

An efficient approach for the elevator button manipulation using the visual-based self-driving mobile manipulator

Toan

Jeong²,

Jo³

2022

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Deep Learning-based Intelligent Reading Recognition Method of the Digital Multimeter

Zhou

Peng

2021

2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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Electronic Online Handwriting Character Recognition System Using Arduino Platform

et al. 2017

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This paper proposes an online prototype approach of handwriting character recognition system using a microcontroller. The main contribution of this work is the simple method of translating a handwriting input from analog to a digital font using XOR bit-wise operation. This system recognizes characters and numbers in natural handwriting with a stylus. This electronic system is used to improve the technology from the use of a bulky keyboard system to a portable and convenient way which is more suitable for smaller electronic devices nowadays such as smart phone, tablet and etc. In order to construct the system, a Arduino Mega is used as the microcontroller along with the Arduino TFT Touch Shield and an LCD screen as the input and output respectively as the hardware components. For the software part, this system uses C language and Arduino software (IDE). The recognition result achieved is 80.0%.

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Real-Time LCD Digit Recognition System

Cited by 3 publications

References 12 publications

An efficient approach for the elevator button manipulation using the visual-based self-driving mobile manipulator

An efficient approach for the elevator button manipulation using the visual-based self-driving mobile manipulator

Deep Learning-based Intelligent Reading Recognition Method of the Digital Multimeter

Electronic Online Handwriting Character Recognition System Using Arduino Platform

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