SYSTEM AND METHOD FOR DISPLAYING RESULTS OF AN IMAGE PROCESSING SYSTEM THAT HAS MULTIPLE RESULTS TO ALLOW SELECTION FOR SUBSEQUENT IMAGE PROCESSING

1 . A method of processing an initial digital image that comprises a foreground object and a background, the method comprising:

displaying the initial digital image on a display;

performing a plurality of instances of a first image segmentation technique to the initial digital image, wherein the first image segmentation technique differentiates between the foreground object and the background in the initial digital image, thereby creating a plurality of processed digital images of the initial digital image, wherein

a first instance of the first image segmentation technique uses a different parameter set than a second instance of the first image segmentation technique; and

each respective instance of the first image segmentation technique creates a processed image corresponding to the respective instance of the first image segmentation technique;

concurrently displaying on the display each processed image in the plurality of processed images at a time when the initial digital image is also displayed on the display; and

receiving a selection of a processed image in the plurality of processed images for further processing.

2 . The method of claim 1 , wherein

a first processed digital image corresponding to a first instance of the first image segmentation technique in the plurality of processed digital images contains the background of the initial digital image; and

pixel values in all or a portion of the background in the first processed digital image differ from pixel values for corresponding pixels in all or a portion of the background in the initial digital image.

3 . The method of claim 1 , wherein

the plurality of instances of the first image segmentation technique comprises three or more instances; and

the plurality of processed digital images comprises three or more images.

4 . The method of claim 1 , wherein

the performing step further comprises performing a plurality of instances of a second image processing technique to the digital image;

the second image segmentation technique differentiates between the foreground object and the background in the initial image thereby creating processed digital images of the initial digital image in the plurality of processed images;

a first instance of the second image segmentation technique in the plurality of instances of the second image processing technique uses a different parameter set than a second instance of the second image segmentation technique; and

each respective instance of the second image segmentation technique creates a processed image corresponding to the respective instance of the first image segmentation technique.

5 . The method of claim 1 , wherein

the first image segmentation technique is a thresholding technique;

the parameter set for the first instance of the first image segmentation technique comprises a first threshold value;

the parameter set for the second instance of the first image segmentation technique comprises a second threshold value; and

the first threshold value is different than the second threshold value.

6 . The method of claim 1 , wherein the first image segmentation technique is a clustering method, a histogram-based method, an edge detection method, a region growing method, a level set method, a graph partitioning method, a watershed transformation, a model segmentation method, a multi-scale segmentation, a semi-automatic segmentation, or a neural network segmentation.

7 . A system for processing an initial digital image that comprises a foreground object and a background, the system comprising:

means for displaying the initial digital image on a display;

means for performing a plurality of instances of a first image segmentation technique to the initial digital image, wherein the first image segmentation technique differentiates between the foreground object and the background in the initial digital image, thereby creating a plurality of processed digital images of the initial digital image, wherein

a first instance of the first image segmentation technique uses a different parameter set than a second instance of the first image segmentation technique; and

each respective instance of the first image segmentation technique creates a processed image corresponding to the respective instance of the first image segmentation technique;

means for concurrently displaying on the display each processed image in the plurality of processed images at a time when the initial digital image is also displayed on the display; and

means for receiving a selection of a processed image in the plurality of processed images for further processing.

8 . The system of claim 7 , wherein

a first processed digital image corresponding to a first instance of the first image segmentation technique in the plurality of processed digital images contains the background of the initial digital image; and

pixel values in all or a portion of the background in the first processed digital image differ from pixel values for corresponding pixels in all or a portion of the background in the initial digital image.

9 . The system of claim 7 , wherein

the plurality of instances of the first image segmentation technique comprises three or more instances; and

the plurality of processed digital images comprises three or more images.

10 . The system of claim 7 , wherein

the means for performing further comprises means for performing a plurality of instances of a second image processing technique to the digital image;

the second image segmentation technique differentiates between the foreground object and the background in the initial image thereby creating processed digital images of the initial digital image in the plurality of processed images;

a first instance of the second image segmentation technique in the plurality of instances of the second image processing technique uses a different parameter set than a second instance of the second image segmentation technique; and

each respective instance of the second image segmentation technique creates a processed image corresponding to the respective instance of the first image segmentation technique.

11 . The system of claim 7 , wherein

the first image segmentation technique is a thresholding technique;

the parameter set for the first instance of the first image segmentation technique comprises a first threshold value;

the parameter set for the second instance of the first image segmentation technique comprises a second threshold value; and

the first threshold value is different than the second threshold value.

12 . The system of claim 7 , wherein the first image segmentation technique is a clustering method, a histogram-based method, an edge detection method, a region growing method, a level set method, a graph partitioning method, a watershed transformation, a model segmentation method, a multi-scale segmentation, a semi-automatic segmentation, or a neural network segmentation.

13 . A computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein for processing an initial digital image that comprises a foreground object and a background, the computer program mechanism comprising instructions for:

displaying the initial digital image on a display;

performing a plurality of instances of a first image segmentation technique to the initial digital image, wherein the first image segmentation technique differentiates between the foreground object and the background in the initial digital image, thereby creating a plurality of processed digital images of the initial digital image, wherein

a first instance of the first image segmentation technique uses a different parameter set than a second instance of the first image segmentation technique; and

each respective instance of the first image segmentation technique creates a processed image corresponding to the respective instance of the first image segmentation technique;

concurrently displaying on the display each processed image in the plurality of processed images at a time when the initial digital image is also displayed on the display; and

receiving a selection of a processed image in the plurality of processed images for further processing.

14 . The computer program product of claim 13 , wherein

a first processed digital image corresponding to a first instance of the first image segmentation technique in the plurality of processed digital images contains the background of the initial digital image; and

pixel values in all or a portion of the background in the first processed digital image differ from pixel values for corresponding pixels in all or a portion of the background in the initial digital image.

15 . The computer program product of claim 13 , wherein

the plurality of instances of the first image segmentation technique comprises three or more instances; and

the plurality of processed digital images comprises three or more images.

16 . The computer program product of claim 13 , wherein

the instructions for performing further comprises instructions for performing a plurality of instances of a second image processing technique to the digital image;

the second image segmentation technique differentiates between the foreground object and the background in the initial image thereby creating processed digital images of the initial digital image in the plurality of processed images;

a first instance of the second image segmentation technique in the plurality of instances of the second image processing technique uses a different parameter set than a second instance of the second image segmentation technique; and

each respective instance of the second image segmentation technique creates a processed image corresponding to the respective instance of the first image segmentation technique.

17 . The computer program product of claim 13 , wherein

the first image segmentation technique is a thresholding technique;

the parameter set for the first instance of the first image segmentation technique comprises a first threshold value;

the parameter set for the second instance of the first image segmentation technique comprises a second threshold value; and

the first threshold value is different than the second threshold value.

18 . The computer program product of claim 13 , wherein the first image segmentation technique is a clustering method, a histogram-based method, an edge detection method, a region growing method, a level set method, a graph partitioning method, a watershed transformation, a model segmentation method, a multi-scale segmentation, a semi-automatic segmentation, or a neural network segmentation.

19 . A computer, comprising:

a main memory;

a processor; and

one or more programs for processing an initial digital image that comprises a foreground object and a background, stored in the main memory and executed by the processor, the one or more programs collectively including instructions for:

displaying the initial digital image on a display;

performing a plurality of instances of a first image segmentation technique to the initial digital image, wherein the first image segmentation technique differentiates between the foreground object and the background in the initial digital image, thereby creating a plurality of processed digital images of the initial digital image, wherein

a first instance of the first image segmentation technique uses a different parameter set than a second instance of the first image segmentation technique; and

each respective instance of the first image segmentation technique creates a processed image corresponding to the respective instance of the first image segmentation technique;

concurrently displaying on the display each processed image in the plurality of processed images at a time when the initial digital image is also displayed on the display; and

receiving a selection of a processed image in the plurality of processed images for further processing.

20 . The computer of claim 19 , wherein

a first processed digital image corresponding to a first instance of the first image segmentation technique in the plurality of processed digital images contains the background of the initial digital image; and

pixel values in all or a portion of the background in the first processed digital image differ from pixel values for corresponding pixels in all or a portion of the background in the initial digital image.

21 . The computer of claim 20 , wherein

the plurality of instances of the first image segmentation technique comprises three or more instances; and

the plurality of processed digital images comprises three or more images.

22 . The computer of claim 20 , wherein

the instructions for performing further comprises instructions for performing a plurality of instances of a second image processing technique to the digital image;

the second image segmentation technique differentiates between the foreground object and the background in the initial image thereby creating processed digital images of the initial digital image in the plurality of processed images;

a first instance of the second image segmentation technique in the plurality of instances of the second image processing technique uses a different parameter set than a second instance of the second image segmentation technique; and

each respective instance of the second image segmentation technique creates a processed image corresponding to the respective instance of the first image segmentation technique.

23 . The computer of claim 20 , wherein

the first image segmentation technique is a thresholding technique;

the parameter set for the first instance of the first image segmentation technique comprises a first threshold value;

the parameter set for the second instance of the first image segmentation technique comprises a second threshold value; and

the first threshold value is different than the second threshold value.

24 . The computer of claim 20 , wherein the first image segmentation technique is a clustering method, a histogram-based method, an edge detection method, a region growing method, a level set method, a graph partitioning method, a watershed transformation, a model segmentation method, a multi-scale segmentation, a semi-automatic segmentation, or a neural network segmentation.