Masahiko Sugimura

An FPGA-accelerated partial duplicate image retrieval engine for a document search system

In this paper, we introduce an FPGA-accelerated partial image retrieval engine, suitable for a visualized document search system. To achieve efficient sharing and reuse of digitized documents, this system has the function of partial duplicate image retrieval. To meet the demand for stability and speed, we introduced a brute-force matching of the BRIEF descriptor with two step scheme and an FPGA accelerator with a thoroughly parallelized and pipelined architecture to educe the potential of the FPGA. The FPGA accelerator significantly improves the runtime performance of the engine. It is about 65 times better than a CPU-based solution on average. Ultimately, we developed a prototype document search system, and the proposed engine contributes to the intuitive retrieval and quick response of the system.

An FPGA-accelerated partial image matching engine for massive media data searching systems

We propose and demonstrate an FPGA-accelerated partial-image-matching engine for massive media-data searching systems. To take advantage of FPGA, a highly parallelized and pipelined architecture with an application-specific calculation was adopted. Our prototype system achieves 32 times better runtime performance than a CPU-based solution.

Industry Track: An Image Classification and Browsing System for Farm Inspection

When a farmer shares information about farm situation or events with other farmers, he often uses pictures (images) taken during farm inspection for visual communication. However, it may take much time for the farmers to find the desired images from a large amount of images accumulated every day. Furthermore, the contents of the images are diverse (e.g. crop images, soil images, and field images), and the content of the desired images are dependent on the usage scene. Therefore, we develop an image classification and browsing system to suitable for the usage scene. We adopt a typical SVM image classification method using color histogram or layout of brightness as image features. The effectiveness of our system is verified by feasibility study in checking the growth situation of crops. The contribution of this work is the first attempt to apply the image classification and browsing technique to the farm inspection support in agricultural fields.