A kind of trademark image retrieval method
An image retrieval and image technology, applied in digital data information retrieval, instruments, computing, etc., can solve the problems that image features cannot express the high-level semantics of users, problems have not been solved well, and retrieval results are unsatisfactory, etc., to achieve The effect of fast calculation speed, small amount of data, and elimination of wrong matching
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Embodiment 1
[0053] A trademark image retrieval method, comprising the following steps:
[0054] S1: Perform multi-scale feature extraction on the image to be retrieved and the comparison image in the image database;
[0055] S2: Carry out similarity matching between the image features to be retrieved and the compared image features between global scales;
[0056] S3: filter the correct match;
[0057] S4: candidate similar region segmentation;
[0058] S5: Similarity matching between local scales in the region, sorting the comparison images according to the size of the matching similarity.
Embodiment 2
[0060] A trademark image retrieval method, comprising the following steps:
[0061] S1: Multi-scale feature extraction is performed on the image to be retrieved and the comparison image in the image database; multiple sliding windows of different scales are used to segment the regions of the image to be retrieved and the comparison image, and image features in the sliding window window are extracted;
[0062] Include the following steps:
[0063] (1) Extract the gradient direction histogram feature of the image pixel in the sliding window window;
[0064] (2) Gradient orientation histogram quantization coding;
[0065] (3) Normalization;
[0066] (4) Spatial distribution description, and cascaded gradient direction histogram and spatial distribution.
[0067] S2: Carry out similarity matching between the features of the image to be retrieved and the features of the compared image on a global scale; slide the sliding window in the image to be retrieved, traverse all the wind...
Embodiment 3
[0074] A trademark image retrieval method, comprising the following steps:
[0075] S1: Multi-scale feature extraction is performed on the image to be retrieved and the comparison image in the image database; multiple sliding windows of different scales are used to segment the regions of the image to be retrieved and the comparison image, and image features in the sliding window window are extracted;
[0076] Include the following steps:
[0077] (1) Extract the gradient direction histogram feature of the image pixel in the sliding window window;
[0078] (2) Gradient orientation histogram quantization coding;
[0079] (3) Normalization;
[0080] (4) Spatial distribution description, and cascade gradient direction histogram and spatial distribution;
[0081] Step (1), calculate the horizontal gradient and vertical gradient of the image pixel, using the direction template [-1,0,1], the calculation rule is [G h ,G v ] = gradient(F),
[0082] Step (2), the direction angle...
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