Method for identifying a person from a detected eye image
First Claim
1. A method for identifying a person by using a detected eye image, the method comprising steps of:
- discriminating an image, this is differentiated between a detected personal image and a background scene,compressing the discriminated image to one-seventh of its original size,decoding the compressed image into a binary-code image by utilizing multi-critical values,defining a bright portion of the binary-code image for a searching region,generating a histogram for a surveying region,comparing a specified histogram of the searching region with various templates to sort-out a similar facial regions and select at least one similar eye region among the similar facial regions, anddetermining an eye position, this is closely matched among the selected similar eye regions through a characteristic analysis.
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Abstract
A method for identifying a person from the detected eye image has been developed, the steps of which are: (a) discriminating the image difference by comparing the detected personal eye image with the simple background scene, and compressing the corresponding discriminated eye image; (b) decoding the compressed image to the binary coded image by utilizing multi-critical values; (c) defining only the bright region of the binary coded image as the surveying area; (d) generating the histogram for the surveying area; (e) comparing the specified histogram of the surveying area with various pre-stored templates to sort-out the similar facial groups and pick at least one similar eye region among the similar facial groups, and (f) determining the best matched eye appearance through the character analysis of the selected similar eye regions.
26 Citations
4 Claims
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1. A method for identifying a person by using a detected eye image, the method comprising steps of:
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discriminating an image, this is differentiated between a detected personal image and a background scene, compressing the discriminated image to one-seventh of its original size, decoding the compressed image into a binary-code image by utilizing multi-critical values, defining a bright portion of the binary-code image for a searching region, generating a histogram for a surveying region, comparing a specified histogram of the searching region with various templates to sort-out a similar facial regions and select at least one similar eye region among the similar facial regions, and determining an eye position, this is closely matched among the selected similar eye regions through a characteristic analysis. - View Dependent Claims (2, 3, 4)
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Specification