Notice of retraction
Vol. 32, No. 8(2), S&M2292

ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

Instructions to authors
English    日本語

Instructions for manuscript preparation
English    日本語

Template
English

Publisher
 MYU K.K.
 Sensors and Materials
 1-23-3-303 Sendagi,
 Bunkyo-ku, Tokyo 113-0022, Japan
 Tel: 81-3-3827-8549
 Fax: 81-3-3827-8547

MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.


MYU Research

(proofreading and recording)


MYU K.K.
(translation service)


The Art of Writing Scientific Papers

(How to write scientific papers)
(Japanese Only)

Sensors and Materials, Volume 32, Number 6(1) (2020)
Copyright(C) MYU K.K.
pp. 1969-1979
S&M2233 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2020.2788
Published: June 10, 2020

Image Shadow Detection and Removal in Autonomous Vehicle Based on Support Vector Machine [PDF]

Tianjun Zhu and Xiaoxuan Yin

(Received December 26, 2019; Accepted April 28, 2020)

Keywords: support vector machine, shadow detection, autonomous vehicle

An image shadow in an autonomous vehicle often causes failures in image segmentation and object tracking and in recognition algorithms. In this paper, a shadow detection method based on a support vector machine (SVM) is proposed. Firstly, an RGB image was converted to LAB color space, and a shadow detection model based on an SVM was obtained by training the image with a shadow. Then, the image was divided into a shadow region, a shadow boundary, and a light region. Moreover, the light intensity in the shadow region was adjusted by eliminating the pixel difference between the shadow region and the light region. Meanwhile, the image gradient was established within the shadow boundary, and the boundary shadow was replaced by smooth interpolation to achieve a smooth transition from the light region to the shadow region. Finally, a clear image without a shadow was recovered using wavelet gradient data. Experimental results show that this method can detect the shadow region in an image and reproduce the image without the shadow effectively.

Corresponding author: Tianjun Zhu


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Tianjun Zhu and Xiaoxuan Yin, Image Shadow Detection and Removal in Autonomous Vehicle Based on Support Vector Machine, Sens. Mater., Vol. 32, No. 6, 2020, p. 1969-1979.



Forthcoming Regular Issues


Forthcoming Special Issues

Special Issue on Perceptual Deep Learning in Computer Vision and its Application
Guest editor, Chih-Hsien Hsia (National Ilan University)


Special issue on Novel Materials and Sensing Technologies on Electronic and Mechanical Devices (1)
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Hsien-Wei Tseng (Longyan University)
Call for paper


Special Issue on New Trends in Smart Sensor Systems
Guest editor, Takahiro Hayashi (Kansai University)
Call for paper


Special Issue on International Conference on BioSensors, BioElectronics, BioMedical Devices, BioMEMS/NEMS and Applications 2019 (Bio4Apps 2019)
Guest editor, Hirofumi Nogami and Masaya Miyazaki (Kyushu University)
Conference website
Call for paper


Special Issue on Materials, Devices, Circuits, and Analytical Methods for Various Sensors (4)
Guest editor, Chien-Jung Huang (National University of Kaohsiung), Cheng-Hsing Hsu (National United University), Ja-Hao Chen (Feng Chia University), and Wei-Ling Hsu (Huaiyin Normal University)
Conference website


Special Issue on Geomatics Technologies for the Realization of Smart Cities
Guest editor, He Huang and XiangLei Liu (Beijing University of Civil Engineering and Architecture)
Call for paper


Copyright(C) MYU K.K. All Rights Reserved.