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All weather robot vision

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	All weather robot visionby Jiandong Tian.
作者:	Tian, Jiandong.
出版者:	Singapore :Springer Singapore :2022.
面頁冊數:	x, 311 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Robot vision.
電子資源:	https://doi.org/10.1007/978-981-16-6429-8
ISBN:	9789811664298$q(electronic bk.)

All weather robot vision
Tian, Jiandong.

All weather robot vision[electronic resource] /by Jiandong Tian. - Singapore :Springer Singapore :2022. - x, 311 p. :ill., digital ;24 cm. - Research on intelligent manufacturing,2523-3394. - Research on intelligent manufacturing..

Introduction -- Robot vision feasible calculations for outdoor illumination and reflectance -- Shadow modelling and intrinsic lighting decomposition -- Shadow/highlight detection and removal -- Rain, snowflake and fog removal -- Underwater scattering modeling and removal -- Discussion and Conclusions.

Complex illumination and meteorological conditions can significantly limit the robustness of robotic vision systems. This book focuses on image pre-processing for robot vision in complex illumination and dynamic weather conditions. It systematically covers cutting-edge models and algorithms, approaching them from a novel viewpoint based on studying the atmospheric physics and imaging mechanism. It provides valuable insights and practical methods such as illumination calculations, scattering modeling, shadow/highlight detection and removal, intrinsic image derivation, and rain/snow/fog removal technologies that will enable robots to be effective in diverse lighting and weather conditions, i.e., ensure their all-weather operating capacity. As such, the book offers a valuable resource for researchers, graduate students and engineers in the fields of robot engineering and computer science.

ISBN: 9789811664298$q(electronic bk.)

Standard No.: 10.1007/978-981-16-6429-8doiSubjects--Topical Terms:

204627
Robot vision.

LC Class. No.: TJ211.3 / .T53 2022

Dewey Class. No.: 629.892637

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505 0 $a Introduction -- Robot vision feasible calculations for outdoor illumination and reflectance -- Shadow modelling and intrinsic lighting decomposition -- Shadow/highlight detection and removal -- Rain, snowflake and fog removal -- Underwater scattering modeling and removal -- Discussion and Conclusions.
520 $a Complex illumination and meteorological conditions can significantly limit the robustness of robotic vision systems. This book focuses on image pre-processing for robot vision in complex illumination and dynamic weather conditions. It systematically covers cutting-edge models and algorithms, approaching them from a novel viewpoint based on studying the atmospheric physics and imaging mechanism. It provides valuable insights and practical methods such as illumination calculations, scattering modeling, shadow/highlight detection and removal, intrinsic image derivation, and rain/snow/fog removal technologies that will enable robots to be effective in diverse lighting and weather conditions, i.e., ensure their all-weather operating capacity. As such, the book offers a valuable resource for researchers, graduate students and engineers in the fields of robot engineering and computer science.
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