Tokyo, Japan

Hitoshi Ichinohe


Average Co-Inventor Count = 3.0

ph-index = 1

Forward Citations = 17(Granted Patents)


Company Filing History:


Years Active: 1996

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1 patent (USPTO):Explore Patents

Title: Hitoshi Ichinohe: Innovator in Character-Feature Extraction Technology

Introduction

Hitoshi Ichinohe is a notable inventor based in Tokyo, Japan. He has made significant contributions to the field of feature recognition technology, particularly through his innovative patent related to character-feature extraction. His work has implications for various applications in image processing and recognition systems.

Latest Patents

Ichinohe holds a patent for a character-feature extraction device. This invention describes a feature recognition method and apparatus that converts digitized two-dimensional patterns or images of characters into vectors. The vectors undergo propagation and stopping operations, which are subject to various tests to generate a list of unique features about the identified pattern. The identified features are then mathematically compared to a previously created feature library until a match is found. Additionally, to enhance the speed of three-dimensional feature-extraction processing, the vector-extraction positions on a pattern are converted into flags and stored in a motion-flag memory.

Career Highlights

Throughout his career, Hitoshi Ichinohe has worked with prominent companies such as Fuji Electric Co., Ltd. and Fujifacom Corporation. His experience in these organizations has contributed to his expertise in the field of technology and innovation.

Collaborations

Ichinohe has collaborated with notable individuals in his field, including Yasuo Hongo and Masatoshi Okada. These collaborations have likely enriched his work and expanded the impact of his inventions.

Conclusion

Hitoshi Ichinohe's contributions to character-feature extraction technology highlight his innovative spirit and dedication to advancing the field of image recognition. His patent reflects a significant step forward in the efficiency and accuracy of feature recognition systems.

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