Region-based image recognition method
First Claim
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1. A region-based image recognition method, comprising the steps of:
- segmenting an input image into a plurality of regions;
extracting a feature of each region; and
classifying a region by inputting its feature into a classifier.
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Abstract
A region-based image recognition method. First, an input image is segmented into a plurality of regions, and the color feature, texture feature, shape feature, position feature and size feature of each region are extracted. Then, the regions are classified by inputting its features into a classifier. The classifier can be a set of decision rules, a neural network model, or a Bayesian classifier.
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14 Claims
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1. A region-based image recognition method, comprising the steps of:
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segmenting an input image into a plurality of regions;
extracting a feature of each region; and
classifying a region by inputting its feature into a classifier. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A region-based image recognition method, comprising the steps of:
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segmenting an input image into a plurality of regions;
extracting the color feature, texture feature, shape feature, position feature and size feature of each region; and
classifying a region as skin or not by inputting its features into a classifier. - View Dependent Claims (12, 13, 14)
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Specification