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2nd EAI International Conference on Robotic Sensor Networks

August 25–26, 2018 | Kitakyushu, Japan

Prof. Hyoungseop Kim

Kyushu Institute of Technology, Japan

Hyoungseop Kim received his B.A. degree in electrical engineering from Kyushu Institute of Technology in 1994, the M.E and Ph.D. degree from Kyushu Institute of Technology in 1996 and 2001, respectively. He is a professor in the Department of Mechanical and Control Engineering at Kyushu Institute of Technology. His research interests are focus on medical application of image analysis. He is currently working on automatic segmentation of multi-organ of abdominal CT image, and temporal subtraction of thoracic CT image sets. He is a member of IEEE, The society of Instrument and Control Engineers of Japan, and The Institute of Electronics, Information and Communication Engineers of Japan.

Title: A Computer Aided Diagnosis System for for Sclerotic Bone Metastasis in CT Images

Cancer is the leading cause of death in Japan and worldwide. Bone metastases are tumors that occur when cancer cells break away from the lung, breast etc. where they started growing and move into bone tissue. We proposed a new image registration method for detection of sclerotic bone metastasis in CT images between current and previous image. We evaluated performance of our proposed method and satisfactory experimental results were obtained.

Prof. Yujie Li

Fukuoka University, Japan

Yujie Li received the B.S. degree in Computer Science and Technology from Yangzhou University in 2009. She received M.S. degrees in Electrical Engineering from Kyushu Institute of Technology and Yangzhou University in 2012, respectively. She received a Ph.D. degree from Kyushu Institute of Technology in 2015. From 2016 to 2017, she was a Lecturer in Yangzhou University. Currently, she is an Assistant Professor in Fukuoka University, Japan and JSPS Research Fellow in Kyushu Institute of Technology, Japan. Her research interests include computer vision, sensors, and image segmentation.

Title: Optical Image Quality Improvement for Underwater Environment

There have been increased developments in deep-sea exploration using autonomous underwater vehicles (AUVs) and unmanned underwater vehicles (UUVs). However, the contrast of underwater images is still a major issue for application. It is difficult to acquire clear underwater images around underwater vehicles. Different from the common images, underwater images suffer from poor visibility due to the medium scattering and light distortion. First of all, capturing images underwater are difficult, mostly due to attenuation caused by light. The random attenuation of the light mainly causes the haze appearance along with the part of the light scattered back from the water. In particular, the objects at a distance of more than 10 meters are almost indistinguishable because of absorption. Furthermore, when the artificial light is employed, it can cause a distinctive footprint on the seafloor. In this talk, I will introduce the image enhancement, and color correction and segmentation methods for solving these issues.


Prof. JooKooi Tan

Associate Professor

Department of Mechanical and Control Engineering

Kyushu Institute of Technology, Japan

Joo Kooi TAN obtained Ph.D from Kyushu Institute of Technology. She is presently with Department of Mechanical and Control Engineering in the same institute as Associate Professor. Her current research interests include three-dimensional shape/motion recovery, objects detection and its motion recognition from an ego camera. She was awarded SICE Kyushu Branch Young Author’s Award in 1999, the AROB10th Young Author’s Award in 2004, Young Author’s Award from IPSJ of Kyushu Branch in 2004 and BMFSA Best Paper Awards in 2008, 2010, 2013 and 2015. She is a member of IEEE, and The Information Processing Society of Japan.

Title: MY VISION System-Based Recognition of Ambient Environmental Objects and Its Application

The number of people who use a mobile communication system while walking outdoors has been more and more increasing all over the world. Accordingly, unexpected accidents caused by carelessness of such people have also been increasing between a walker and the objects like an approaching walker, a bicycle or some obstacles in the environment surrounding him/her.

To prevent such accidents, we have been developing ‘a virtual (or the third) eye of a person’ called MY VISION for recognition and analysis of those objects in a momentarily changing real environment around him/her. The system can be applied not only to ordinary people but also to visually impaired.

In the presentation, recent technical achievements will be introduced with some demonstration videos.