Image analysis – Pattern recognition – Classification
Reexamination Certificate
1998-09-30
2003-08-12
Mehta, Bhavesh M. (Department: 2625)
Image analysis
Pattern recognition
Classification
C382S165000, C382S170000
Reexamination Certificate
active
06606411
ABSTRACT:
FIELD OF THE INVENTION
The invention relates generally to the field of image processing having image understanding that automatically classifies pictures by events and the like and, more particularly, to such automatic classification of pictures by time and date analysis and by block-based analysis which selectively compares blocks of the images with each other.
BACKGROUND OF THE INVENTION
Pictorial images are often classified by the particular event, subject or the like for convenience of retrieving, reviewing, and albuming of the images. Typically, this has been achieved by manually segmenting the images, or by the below-described automated method. The automated method includes grouping by color, shape or texture of the images for partitioning the images into groups of similar image characteristics.
Although the presently known and utilized methods for partitioning images are satisfactory, there are drawbacks. The manual classification is obviously time consuming, and the automated process, although theoretically classifying the images into events, is susceptible to miss-classification due to the inherent inaccuracies involved with classification by color, shape or texture.
Consequently, a need exists for overcoming the above-described drawbacks.
SUMMARY OF THE INVENTION
The present invention is directed to overcoming one or more of the problems set forth above. Briefly summarized, according to one aspect of the present invention, the invention resides in a method for automatically classifying images into events, the method comprising the steps of: receiving a plurality of images having either or both date and/or time of image capture; determining one or more largest time differences of the plurality of images based on clustering of the images; and separating the plurality of images into the events based on having one or more boundaries between events which one or more boundaries correspond to the one or more largest time differences.
These and other aspects, objects, features and advantages of the present invention will be more clearly understood and appreciated from a review of the following detailed description of the preferred embodiments and appended claims, and by reference to the accompanying drawings.
ADVANTAGEOUS EFFECT OF THE INVENTION
The present invention has the advantage of improved classification of images by utilizing both date and time information and block-based comparison that checks for similarity of subject and background in the images. If date and time information is not available, then the block-based analysis may be used as the sole basis for classification.
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“Introduction to Statistical Pattern Recognition” by Keinosuke Fukanaga. From Introduction to Statistical Pattern Recognition, Boston, Academic, US, pp 508-518.
“Models for Time Coalescence in Event Logs” by Jeffrey P. Hansen and Daniel P. Siewiorek. Fault-Tolerant Parallel and Distributed Systems, 1992. Digest of Papers., 1992. IEEE Workshop on Amherst, MA, USA. Jul. 6-7, 1992, Los Alamitos, CA, USA, IEEE Comput. Soc. US, Jul. 6, 1992, pp. 221-227.
Loui Alexander C.
Pavie Eric S.
Azarian Seyed
Eastman Kodak Company
Mehta Bhavesh M.
Woods David M.
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