Development of High-Speed Fish Pattern Recognition System with Color Image Multi-DSP

彩色图像多DSP高速鱼纹识别系统的研制

• 批准号: 06805088
• 负责人: MATSUO Hirofumi
• 金额: $ 0.77万
• 依托单位: Nagasaki University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for General Scientific Research (C)
• 财政年份: 1994
• 资助国家: 日本
• 起止时间: 1994 至 1995
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-06805088/
• 关键词: Color Image Processing; Parallel Processing; Multi-Processor; 魚種識別; テクスチャ解析; パターン認識; 同時生起行列; ディジタル・シグナル・プロセッサ; 可変画面分割方式

A new color image processing system with multi-DSP is constructed and applied to the pattern recognition of fish species, the shapes of which are very similar but the colors and/or patterns of which are different. This system has a function of variable partition of picture. Therefore, the size, position and number of processing regions can be varied flexibly and dynamically for each processing task. Also, the proposd system consists of the CCD camera, the interface unit, the pixel processor unit, the system controller and the host computer. The high-speed feature extraction of fish is presented as an example of the application of the proposed system. In this application, the shape features of fish are extracted at first, and then the color features are extracted from several small regions of fish and characterized by the co-occurrence matrix. Further, the classification of fish species is realized by the method of multi-level slice classifier. After discussing the relationship between the number of feature parameters for pattern recognition and the reliability of discrimination, we proceed to clarify the configuration of the parallel image processing system for high-speed fish pattern recognition in detail. Since the proposed approach is suitable for the parallel image processing system, the high-speed recognition time of 55 ms per a fish can be achieved.

构建了一种基于多dsp的彩色图像处理系统，并将其应用于形状非常相似但颜色和图案不同的鱼类的模式识别。该系统具有图像的可变分割功能。因此，对于每个加工任务，加工区域的大小、位置和数量可以灵活动态地变化。该系统由CCD摄像机、接口单元、像素处理器单元、系统控制器和上位机组成。以鱼类的高速特征提取为例，介绍了该系统的应用。在该应用中，首先提取鱼的形状特征，然后从鱼的几个小区域中提取颜色特征，并用共现矩阵进行特征化。在此基础上，采用多级切片分类器实现了对鱼类的分类。在讨论了模式识别特征参数数量与识别可靠性之间的关系后，详细阐述了高速鱼类模式识别并行图像处理系统的配置。由于该方法适用于并行图像处理系统，因此可以实现每条鱼55 ms的高速识别时间。

项目成果

Fujio Kurokawa: "Algorithm and Configuration of the Image Processing System for High-Speed Fish Pattern Recognition" Proceedings of the 25th Joint Conference on Imaging Technology. Vol.26. 31-34 (1995)

黑川富士​​夫：《高速鱼类模式识别图像处理系统的算法和配置》第25届成像技术联席会议论文集。

黒川不二雄: "テクスチャ解析による魚体の色特徴抽出について" 画像工学コンファレンス論文集. 25. 79-82 (1994)

Fujio Kurokawa：“通过纹理分析提取鱼体的颜色特征”图像工程会议论文集 25. 79-82 (1994)。

Fujio Kurokawa: "High-Speed Color Image Processing System with Flexible Partition of a Picture and Its Application to Fish Pattern Recognition" Proceedings of the 25th Joint Conference on Imaging Technology. Vol.25. 75-78 (1994)

黑川富士​​夫：“具有图像灵活分区的高速彩色图像处理系统及其在鱼纹识别中的应用”第25届成像技术联席会议论文集。

黒川不二雄: "高速魚種認識のためのアルゴリズムと画像処理システムの構成について" 1995年第26回画像工学コンファレンス. 26. 31-34 (1995)

黑川富士​​夫：“关于高速鱼种识别的算法和图像处理系统的配置”1995年第26届图像工程会议（1995）。

黒川不二雄: "画面の可変分割機能を持つ高速画像処理システムの開発と魚種識別への応用" 画像工学コンファレンス論文集. 25. 75-78 (1994)

Fujio Kurokawa：“具有可变屏幕分割功能的高速图像处理系统的开发及其在鱼类物种识别中的应用”图像工程会议论文集。25. 75-78 (1994)。