Image analysis – Applications – 3-d or stereo imaging analysis
Reexamination Certificate
1998-07-31
2001-05-01
Au, Amelia (Department: 2623)
Image analysis
Applications
3-d or stereo imaging analysis
C382S190000, C345S419000
Reexamination Certificate
active
06226396
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention generally relates to an image data processing system, and in particular to method and system which extracts a target object from an image.
2. Description of the Related Art
There have been proposed several object extraction techniques, for instance, using necessary information which is previously registered, using well-known focusing technology, and using plural image pick-up devices which are arranged in predetermined positional relationship.
According to the technique using the prepared necessary information, when no information can be prepared, the target object cannot be extracted. Further, an expensive distance-measuring device is needed to measure a distance from the principal point in the object side to a part of the object. Furthermore, a distance from the principal point in the image side to the image can be measured using auto-focusing mechanism, but the auto-focusing cannot always operate stably depending on illumination conditions, resulting in reduced reliable measurement.
According to the technique using the focusing technology, an image pickup device images a target object while varying the focal length. Therefore, it is necessary to place the target object within the focal depth.
The technique using plural image pickup devices has been disclosed in Japanese Patent Unexamined Publication No. 10-98646. According to this conventional technique, the target object can be extracted using the three-dimensional coordinates of the contour of the target object. The three-dimensional coordinates of the target object are obtained on the principal of triangulation by using two-dimensional feature points and their point correspondence between the images which are obtained by two image pickup devices, respectively. The technique can provide stable operation without the need of information regarding the target object and with little influence of illumination conditions.
However, the precision of target extraction largely depends on a threshold used to discriminate between the target object and the background and it is difficult to properly determine such a threshold. According the Publication (No. 10-98646), the threshold is determined through human eyes and further the system is not designed to extract two or more target objects but a single object.
SUMMARY OF THE INVENTION
An object of the present invention is to provide object extraction system and method which can extract a target object from an image with precision and stability.
Another object of the present invention is to provide object extraction system and method which can determine a threshold used to discriminate between a target object and its background of an image.
Still another object of the present invention is to provide object extraction system and method which can extract a plurality of target objects from an image.
According to an aspect of the present invention, a first image (e.g. a primary image) and a plurality of second images (e.g. reference images) are generated through a first image pickup device and a plurality of second image pickup devices, respectively, and then a feature region is extracted from the first image, the feature region consisting of a plurality of feature segments each defined by a pair of adjoining feature points. Subsequently, a correspondence point candidate of each of the feature points is extracted from each of the second images. Based on the feature points and the correspondence point candidate of each of the feature points for each of the second images, three-dimensional coordinates corresponding to the feature points are calculated, and the feature region is extracted as a target object from the first image based on the feature points and the three-dimensional coordinates corresponding to the feature points for each of the second images.
The feature region may be extracted according to the following steps: determining point correspondence between the first image and each of the second images using the three-dimensional coordinates for each of the second images; calculating a length difference between a distance of adjoining feature points in the first image and that of their corresponding points in each of the second images; calculating disparities between the feature points in the first image and their corresponding points in the second images; and then extracting the feature region as the target object from the first image when both the length segment length difference and the disparity fall into a segment length difference range and a disparity range, respectively.
According to another aspect of the present invention, the feature region may be extracted according to the following steps: generating the segment length difference range depending on a first distribution of the number of points included in the feature region with respect to the length segment length difference (length difference distribution); generating the disparity range depending on a second distribution of the number of points included in the feature region with respect to the disparity (disparity distribution); and then extracting the feature region as the target object from the first image when both the length difference and the disparity fall into the segment length difference range and the disparity range, respectively.
The feature region may be extracted as the target object from the first image in at least one of the respective cases where the length difference falls into the segment length difference range and where the disparity falls into the disparity range.
The length difference range may be a range where the length difference distribution is larger than a first predetermined threshold level. The disparity range may be a range where the disparity distribution is larger than a second predetermined threshold level. In the case where a plurality of ranges where the disparity distribution is larger than the second predetermined threshold level are detected, a range corresponding to a maximum disparity may be determined to be the disparity range.
REFERENCES:
patent: 4654872 (1987-03-01), Hisano et al.
patent: 5432712 (1995-07-01), Chan
patent: 5867591 (1999-02-01), Onda
patent: 735512A2 (1996-10-01), None
patent: 62-3585 (1987-01-01), None
patent: 7-287764 (1995-10-01), None
patent: 9-81746 (1997-03-01), None
patent: 10-98646 (1998-04-01), None
Dmitry Novik, “Streo Images Data Compression & Digital Stereo Compatible TV”, SPIE Proceedings, Visual Information Processing V, vol. 2753 pp. 1-10, 1996.
Ahmed Samir
Au Amelia
NEC Corporation
Scully Scott Murphy & Presser
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