In this year, we modified the image retrieval scheme by using "GAMON" or Videoprint and investigated its application from the viewpoint of building conventional TV broadcasted content retrieval system connected via network

1.改进了一种特征提取方法以提高其性能：首先，在基于“GAMON”的检索方法中，提出了一种层次化的检索方法，目的是从大存储量的存档视频内容中快速准确地检索出请求的视频。在所提出的方法中，一维DCT操作的时间序列的平均颜色值每帧执行量化的系数和运动图像的特征，最终提取其较低的频率成分。使用此功能作为“GAMON”，快速和准确的图像检索成为可能。作为实验结果之一，图像检索的34个序列（电视广告片：每15秒）的24小时的电视内容档案，在3分钟内执行。此外，我们评估了我们修改后的系统的性能，通过以前的模拟实验的图像检索。结果表明，改进后的系统取得了显著的性能，即比我们以前的系统快13倍，比序列的时间长度快20，000倍.传统电视广播内容检索系统的应用研究：我们假设一个视频内容分发系统通过网络与大型视频内容存档。传统的TV（模拟）内容的质量容易受到它们的接收环境的影响，并且即使来自相同的源，例如，也可以从具有重影的内容中提取不同的特征。为此，我们特意准备了一个包含鬼影内容的图像库，设计并实现了一个基于“GAMON”的MPEG-2图像检索系统，通过模拟实验，实现了非常高的图像检索精度，并且没有多余检测和失败检测。

1. Modification of a feature extraction method to improve its performance : Firstly, in the retrieval method by using "GAMON", we proposed a hierarchical retrieval method, targeted to retrieve the requested video quickly and accurately from the archived video contents in large storage. In the proposed method, one-dimensional DCT operation to a temporal sequence of average color value per frame is executed with quantization of coefficients and moving picture's feature is finally extracted as its lower frequency components. Using this feature as "GAMON", quick and accurate image retrieval becomes possible. As one of experimental results, image retrieval of 34 sequences(TV ads film : each 15 seconds) out of 24-hours-TV content archive, are executed within 3 minutes. Additionally, we evaluated our modified system's performance through previous simulation experiments of image retrieval. As a result, modified system achieved remarkable performance, namely 13 times faster compared to our previous system and 20,000 times faster compared to sequence's time length.2. Application study on conventional TV broadcasted content retrieval system : We assumed a video content distribution system via network with large video content archive. Conventional TV(analog) contents' quality is easily influenced by their receiving environment and even from the same source, different features can be extracted from contents with ghost, for example. Therefore we have intentionally prepared an archive with some contents including ghosts, designed an image retrieval system by using "GAMON" for MPEG-2 images and implemented it. Through simulation experiments, very high accurate image retrieval are done with results of 0 surplus detection and 0 failure detection.