Method for extracting target closed contour based on shape prior
A closed contour and target technology, which is applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems of no occlusion, illumination robustness, elastic deformation invariance, background noise and internal texture interference, etc.
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Embodiment 1
[0090] The closed contour extraction of embodiment 1 horse
[0091] First, a salient edge map of the input image is obtained. Its working process is described as follows:
[0092] ①Simulate the complex cells in the human primary visual cortex to extract edge segments with specific frequency and orientation from the input image, and filter the image I with a set of odd-symmetric and even-symmetric Gabor filter banks. figure 2(a) The cell receptive field maps of the human primary visual cortex with odd symmetry and even symmetry are respectively given, and the image of the two-dimensional Gabor function in the spatial domain is similar to this.
[0093] ② Simulate the inhibitory effect in the human primary visual cortex, with a normalized difference of Gaussian filter Responses with complex cells p f,θ to represent the convolution. figure 2 (b) Schematic representation of inhibition of classical receptive fields in human primary visual cortex.
[0094] ③Inhibition is add...
Embodiment 2
[0107] Example 2 The Closed Contour Extraction of Pedestrians
[0108] The only difference between the operation of this embodiment and the first embodiment is that when calculating the similarity between the rough contour in the salient edge map and each template, different sizes are used for the template, ranging from 0.5 times the original size of the template to Take 6 sizes at equal intervals between 2 times, and calculate the similarity between the template and the salient edge map under different zoom sizes, so that the size with the highest similarity (that is, the smallest distance between shapes) is the matching size, and the subsequent steps are all in The matching dimensions are made. This is because the size of the pedestrian in the template may be different from that in the image to be processed, and such preprocessing is to make the present invention have scaling invariance.
[0109] Simulating the information processing mechanism of human vision, integrating s...
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Abstract
Description
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Application Information
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