Company Filing History:
Years Active: 2014
Title: Tsung-Chan Li: Innovator in Moving Object Detection
Introduction
Tsung-Chan Li is a prominent inventor based in Taoyuan County, Taiwan. He has made significant contributions to the field of image processing, particularly in the area of moving object detection. His innovative approach has led to the development of a unique method that enhances the accuracy and efficiency of detecting moving objects in images.
Latest Patents
Tsung-Chan Li holds a patent for a "Moving object detection method and image processing system for moving object detection." This invention involves computing a pixel-wise distance of a received image to a reference image to create a distance map. A histogram analysis is then performed on this distance map to derive a distance distribution. The process includes calculating an entropy value of the distance distribution and identifying a peak distance value with the highest occurrence probability. By applying a mapping rule, the entropy value and peak distance value are transformed into a decision threshold value. This threshold is crucial for classifying pixels into foreground and background attributes, ultimately allowing for the identification of moving objects in the current image.
Career Highlights
Tsung-Chan Li is affiliated with the Industrial Technology Research Institute, where he continues to advance research in image processing technologies. His work has garnered attention for its practical applications in various industries, enhancing the capabilities of systems that rely on accurate moving object detection.
Collaborations
He has collaborated with notable colleagues, including Tai-Hui Huang and Wen-Hao Wang, contributing to a dynamic research environment that fosters innovation and development in their field.
Conclusion
Tsung-Chan Li's contributions to moving object detection exemplify the impact of innovative thinking in technology. His patent reflects a significant advancement in image processing, showcasing his dedication to enhancing detection methods. His work continues to influence the field and inspire future innovations.