The main purpose of Codemark is to distribute digital contents using offline media. Due to the main purpose of Codemark, Codemark cannot be used on digital images. It has high robustness on only printed images. This paper presents a new color code called Robust Index Code (RIC for short), which has high robustness on JPEG Compression and Resize targeting digital images. RIC embeds a remote database index to digital images so that users can reach to any digital contents. Experimental results, using our implemented RIC encoder and decoder, have shown high robustness on JPEG Comp. and Resize of the proposed codemark. The embedded database indexes can be extracted 100% on compressed images to 30%. In conclusion, it is able to store all the type of digital products by embedding indexes into digital images to access database, which means it makes a Superdistribution system with digital images realized. Therefore RIC has the potential for new Internet image services, since all the images encoded by RIC are possible to access original products anywhere.

Two schemes for fast identification of JPEG coded images are proposed in this paper. The aim is to identify the JPEG images that are generated from the same original image and have equivalent or different compression ratios. Fast identification can be achieved since the schemes work on the quantized Discrete Cosine Transform (DCT) domain. It is not required to inverse the quantization and the DCT. Moreover, only a few coefficients are commonly required for identification. The first approach can avoid identification leakage or false negative (FN), and probably result in a few false positives (FP). The second approach can avoid both FN and FP, with a slightly higher processing time. By combining the two schemes, a faster and a more perfect identification can be achieved, in which FN and FP can be avoided.

We propose a system that enables us to gather hundreds of images related to one set of keywords provided by a user from the World Wide Web. The system is called Image Collector II. The Image Collector, which we proposed previously, can gather only one or two hundreds of images. We propose the two following improvements on our previous system in terms of the number of gathered images and their precision: (1) We extract some words appearing with high frequency from all HTML files in which output images are embedded in an initial image gathering, and using them as keywords, we carry out a second image gathering. Through this process, we can obtain hundreds of images for one set of keywords. (2) The more images we gather, the more the precision of gathered images decreases. To improve the precision, we introduce word vectors of HTML files embedding images into the image selecting process in addition to image feature vectors.

Intending to contribute to constructing better multimedia network systems, we propose a new concept of image database system of which form of storage is featuring exponential or graceful oblivion and abrupt recollection like the human memory property. By virtue of this property of database storages that is realized by employing hierarchical or pyramidal image coding, the database memory and transmission costs can be significantly reduced. In this paper we will describe the details of the concept, the results of theoretical analysis based on a simplified model which reveals the effectiveness of the proposed system, the structure of an experimental prototype system and the result of an experimental image retrieval service carried out by implementing it over ATM high speed channels.

This paper presents a comprehensive framework for the organization, retrieval, and adaptation of image information and meta-information in image database systems. The multi-level hierarchy of images that emphasizes the composition of visual entities (such as Human, Chair, , etc.) from its constituents (eye, leg, , etc.) is managed by a host architecture that is called the semantic tree. This architecture is shown to integrate description, numeric, and statistic image constituent's information into a compound space that is used as retrieval basis for semantic, sketch, and template image queries and several other composite query types. The core architecture based on which the semantic tree is constructed is shown to offer several new features such as simple prototyping, complex prototyping, low storage requirements, and automatic knowledge acquisition compatibility. The object oriented data model constitutes our comparison basis throughout the paper. Methods (functions) used to access image information are shown to be organized into a separate architecture called the query dictionary. This architecture is shown to offer a convenient hierarchical message passing medium using which a variety of composite queries are constructed. Interaction between semantic trees and the query dictionary is clarified through several examples. It is shown that the semantic tree architecture embraces additional networking semantic intormation through a range of relation representation models, the first of which is introduced in this paper. A new inheritance method called semantic relation spreading is introduced. Comprehensive examples are given to demonstrate the versatility of the new strategy.

Recently, a flexible image database retrieval system where image keywords can be captured automatically is strongly required, in order to manage a practical number of image data successfully. However, image recognition/understanding technology level is not generally sufficient enough to achieve this requirement. In order to overcome this problem, a new type of image database framework is proposed in this paper. In the proposed system, image keywords are extracted in fully-automated fashion by the flexible and generalized image recognition system. Image keywords employed in this system are a collection of recognized objects in the image, where achieved recognition levels are allowed to be intermediate or imperfect. The concept of recognition thesaurus" has been introduced to manage these various abstraction level of kerwords successfully. As an embodiment of this concept, an experimental image database with various types of sports scenes has been implemented and various retrieval evaluations have been performed. Experimental results reveal the effectiveness of the proposed method.