Company Filing History:
Years Active: 2002
Title: Innovations in Color Management by Paul Apostolos Drakopoulos
Introduction
Paul Apostolos Drakopoulos is an accomplished inventor based in Boulder, CO. He has made significant contributions to the field of color management, particularly through his innovative patent that enhances color printer characterization. His work is pivotal in optimizing the process of generating accurate color profiles for printers.
Latest Patents
Drakopoulos holds a patent titled "Color printer characterization using optimization theory and neural networks." This invention introduces a color management method and apparatus that generates image color matching and International Color Consortium (ICC) color printer profiles using a reduced number of color patch measurements. Traditionally, color printer characterization requires extensive data points and complex interpolation techniques. However, Drakopoulos's invention provides an optimization method for performing LAB to CMYK color space conversion, gamut mapping, and gray component replacement. The technology utilizes a feed-forward neural network trained on a basic data set, significantly reducing the number of required color patches while maintaining accuracy.
Career Highlights
Drakopoulos is associated with University Technology Corporation, where he continues to advance his research and development in color management technologies. His innovative approach has garnered attention in the field, showcasing his expertise in applying optimization theory and neural networks to practical applications.
Collaborations
Drakopoulos has collaborated with Ganesh Subbarayan, working together to enhance the capabilities of color management systems. Their partnership has contributed to the development of more efficient and effective color printing solutions.
Conclusion
Paul Apostolos Drakopoulos is a notable inventor whose work in color management has the potential to revolutionize the printing industry. His innovative patent demonstrates the power of optimization theory and neural networks in improving color accuracy and efficiency.