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文件名称:Edge-based-text-region-extraction-from-natural-im
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- 上传时间：2014-12-16
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The basic steps of the edge-based text extraction algorithm are given below
1. Create a Gaussian pyramid by convolving the input image with a Gaussian kernel
and successively down-sample each direction by half. (Levels: 4)
2. Create directional kernels to detect edges at 0, 45, 90 and 135 orientations.
3. Convolve each image in the Gaussian pyramid with each orientation filter.
4. Combine the results of step 3 to create the Feature Map.
5. Dilate the resultant image using a sufficiently large structuring element (7x7 [1])
to cluster candidate text regions together.
6. Create final output image with text in white pixels against a plain black
background.
1. Create a Gaussian pyramid by convolving the input image with a Gaussian kernel
and successively down-sample each direction by half. (Levels: 4)
2. Create directional kernels to detect edges at 0, 45, 90 and 135 orientations.
3. Convolve each image in the Gaussian pyramid with each orientation filter.
4. Combine the results of step 3 to create the Feature Map.
5. Dilate the resultant image using a sufficiently large structuring element (7x7 [1])
to cluster candidate text regions together.
6. Create final output image with text in white pixels against a plain black
background.
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edgebased.m
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