Mouth removal method for red-eye detection and correction
AssigneeSeiko Epson Corporation
InventorsSusan Yang, Jie Wang
Life of this patent
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Abstract
An input image (e.g. a digital RGB color image) is subjected to an eye classifier that is targeted at discriminating a complete eye pattern from any non-eye patterns. The red-eye candidate list with associated bounding boxes that are generated by the red-eye classifier are received. The bounding rectangles are subjected to object segmentation. A connected component labeling procedure is then applied to obtain one or more red regions. The largest red region is then chosen for feature extraction. A number of features are then extracted from this region. Then these features are used to determine if the particular candidate red-eye object is a mouth.
Claims20
A method for determining if a candidate for red-eye removal processing is a mouth, comprising:
- receiving from an eye classifier a plurality of candidate red-eye objects, each of the candidate red-eye objects contained within a bounding rectangle;
- for each particular candidate red-eye object:
- segmenting the candidate red-eye object to obtain a segmented red region within the candidate red-eye object's bounding rectangle;
- extracting a feature kw, defined as the ratio between a width of the segmented red region and a width of the bounding rectangle;
- extracting a feature kh, defined as the ratio between a height of the segmented red region and a height of the bounding rectangle;
- extracting a feature s, defined as the ratio between the width and height of the segmented red region;
- extracting a feature v, defined as a decision score from the eye classifier;
- extracting a feature m, defined as a geometrical relationship between the particular candidate red-eye object and others of the plurality of candidate red-eye objects;
- and
- using the features kw, kh, s, v, and m to determine if the particular candidate red-eye object is a mouth.
One or more non-transitory computer-readable media having computer-readable instructions thereon, which, when executed by a processor, implement a method for determining if a candidate for red-eye removal processing is a mouth, comprising:
- receiving from an eye classifier a plurality of candidate red-eye objects, each of the candidate red-eye objects contained within a bounding rectangle;
- for each particular candidate red-eye object:
- segmenting the candidate red-eye object to obtain a segmented red region within the candidate red-eye object's bounding rectangle;
- extracting a feature kw, defined as the ratio between a width of the segmented red region and a width of the bounding rectangle;
- extracting a feature kh, defined as the ratio between a height of the segmented red region and a height of the bounding rectangle;
- extracting a feature s, defined as the ratio between the width and height of the segmented red region;
- extracting a feature v, defined as a decision score from the eye classifier;
- extracting a feature m, defined as a geometrical relationship between the particular candidate red-eye object and others of the plurality of candidate red-eye objects;
- and
- using the features kw, kh, s, v, and m to determine if the particular candidate red-eye object is a mouth.
An image capture device for determining if a candidate for red-eye removal processing is a mouth, comprising:
- a processor that:
- receives from an eye classifier a plurality of candidate red-eye objects, each of the candidate red-eye objects contained within a bounding rectangle;
- for each particular candidate red-eye object:
- segments the candidate red-eye object to obtain a segmented red region within the candidate red-eye object's bounding rectangle;
- extracts a feature kw, defined as the ratio between a width of the segmented red region and a width of the bounding rectangle;
- extracts a feature kh, defined as the ratio between a height of the segmented red region and a height of the bounding rectangle;
- extracts a feature s, defined as the ratio between the width and height of the segmented red region;
- extracts a feature v, defined as a decision score from the eye classifier;
- extracts a feature m, defined as a geometrical relationship between the particular candidate red-eye object and others of the plurality of candidate red-eye objects;
- and
- uses the features kw, kh, s, v, and m to determine if the particular candidate red-eye object is a mouth.
Dependencies are inferred from the claim text.