Image analysis – Pattern recognition – Classification
Reexamination Certificate
2001-02-02
2003-12-16
Mehta, Bhavesh M. (Department: 2625)
Image analysis
Pattern recognition
Classification
C382S305000, C382S190000, C382S195000, C707S793000, C707S793000
Reexamination Certificate
active
06665442
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to an image retrieval system and an image retrieval method in which characteristic values and/or pieces of attribute information are extracted from pieces of image data such as moving images or static images recorded in analog or digital and in which the retrieval of desired image data is performed by using the extracted characteristic values and/or the pieces of extracted attribute information.
2. Description of Related Art
FIG. 1
shows the configuration of a system as an example of a conventional image retrieval processing system. This system is disclosed in a letter “Synthesis and Evaluation of the Image Database with Fully Automated Keyword Extraction by State Transition Model and Scene Description Language” edited by Institute of Electronic Information and Communication Engineers of Japan, D-II Vol. J79-D-II No.4, pp.476-483, April of 1996. In this system, static images are processed in the image retrieval. That is, an area of each of images is divided into a plurality of segments in an area dividing unit
103
of a preparation unit
101
, and a plurality of keywords are attached to each divided segment. As the keywords, a conception keyword and a scene description keyword are prepared. In a conception keyword extracting unit
104
, a conception keyword
108
of each segment is obtained according to a color and a characteristic value of the segment by using conception keywords respectively allocated to color information in advance. In a scene description keyword describing unit
105
, a predicate relating to “position”, “color”, “shape”, “size”, “direction” or the like is obtained from a plurality of image characteristic values of segments. In the unit
105
, an operation
106
, in which a user
107
selects one predicate from predicates defined in advance and describes the selected predicate, is required, and the selected predicate is output as a scene description keyword
109
. In a retrieval tool
102
, conception keywords and scene description keywords are prepared in advance. A user
111
selects one conception keyword and one scene description keyword as each of keywords
112
from the prepared keywords. In a characteristic identifying unit
110
, an identity of characteristic values is checked by comparing each keyword
112
selected by the user
111
with the conception keyword
108
or the scene description keyword
109
attached to each segment of the image, and an image retrieval processing is performed for the image.
However, in the above-described image retrieval processing system, an identity of characteristic values is checked by using keywords such as conception keywords and scene description keywords selected by the user
112
and keywords attached to each image, and an image retrieval processing is performed according to the characteristic values of each image. Therefore, all images are searched according to only the characteristic values of the images, so that it takes a lot of time to retrieve a desired image.
Also, in the above-described image retrieval processing system, a description method or a storing method of each keyword is not considered. Therefore, it is required that a plurality of image servers relate to a plurality of retrieval tools denoting clients in one-to-one correspondence. As a result, a system, in which many users respectively perform the image retrieval through a network while using various retrieval tools, cannot be provided for the users.
Also, because only static images are processed in the image retrieval, it is difficult to retrieve a desired moving image.
SUMMARY OF THE INVENTION
The present invention is provided to solve the above problems, and a main object of the present invention is to provide an image retrieval system and an image retrieval method in which an image retrieval processing can be efficiently performed.
A subordinate object of the present invention is to provide an image retrieval system and an image retrieval method which does not depend on a plurality of image servers distributed in a network by describing and producing a plurality of retrieval keywords according to a common syntax.
Another subordinate object of the present invention is to provide an image retrieval system and an image retrieval method in which the retrieval of a desired moving image can be easily performed by extracting a characteristic value for each video segment, which is composed of a plurality of frames, in place of the extraction of a characteristic value for each frame when a plurality of keywords are extracted from moving images.
An image retrieval system according to the present invention, comprises a characteristic descriptor producing unit for extracting a plurality of image characteristic values from pieces of input image data and producing a characteristic descriptor for each piece of input image data, an image information storing unit for storing the characteristic descriptors produced in the characteristic descriptor producing unit while holding the correspondence of each characteristic descriptor to one piece of input image data, an attribute list producing unit for producing an attribute list according to a piece of attribute information attached to each piece of input image data, and an image retrieving unit for receiving a first retrieval condition relating to attribute information, searching the attribute list produced in the attribute list producing unit for one piece of attribute information conforming to the first retrieval condition, outputting the piece of attribute information conforming to the first retrieval condition, receiving a second retrieval condition relating to a characteristic descriptor, searching the image information storing unit for one piece of image data conforming to the second retrieval condition and outputting the piece of image data conforming to the second retrieval condition.
Therefore, the retrieval can be efficiently performed.
In an image retrieval system according to the present invention, the attribute list is produced according to a syntax, which defines a data structure of the attribute list, in the attribute list producing unit, and the piece of attribute information conforming to the first retrieval condition is retrieved according to the syntax of the attribute list in the image retrieving unit.
Therefore, the retrieval can be efficiently performed in a short time.
In an image retrieval system according to the present invention, the characteristic descriptors are produced according to a syntax, which defines a data structure of each characteristic descriptor, in the characteristic descriptor producing unit, and the piece of image data conforming to the second retrieval condition is retrieved in the image retrieving unit according to the syntax of the characteristic descriptors.
Therefore, the image retrieval not depending on a plurality of image servers distributed in the network can be performed.
In an image retrieval system according to the present invention, one image characteristic value is extracted in the characteristic descriptor producing unit for each frame, and one characteristic descriptor is produced in the characteristic descriptor producing unit for each video segment composed of a group of frames.
Therefore, the retrieval of a moving image can be easily performed.
In an image retrieval system according to the present invention, each piece of input picture data received in the characteristic descriptor producing unit denotes compressed video data which composes one or more intra-frames and one or more inter-frames, both an average value and a standard deviation are produced as one characteristic descriptor of the intra-frames of the video segment in the characteristic descriptor producing unit by extracting an average matrix of pixel values in a prescribed coding area of one intra-frame for each intra-frame of the video segment, calculating a sum of the average matrices of all intra-frames included in the video segment and calculating both the average value of the average matrices a
Asai Kohtaro
Isu Yoshimi
Nishikawa Hirofumi
Sekiguchi Shun-ichi
Yamada Yoshihisa
Bayat Ali
Mitsubishi Denki & Kabushiki Kaisha
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