Hong Kong dollar texture image version classifying method based on gray-level co-occurrence matrix
A gray-level co-occurrence matrix and Hong Kong dollar technology, which is applied in the direction of instruments, calculations, character and pattern recognition, etc., can solve the problems of the complexity of Hong Kong dollar version recognition
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[0103] In the present embodiment, collect various versions of Hong Kong dollars (Bank of China, HSBC, Standard Chartered): 1000 yuan, 500 yuan, 100 yuan, 50 yuan denominations of different versions (97 editions, 03 editions, 07 editions, 10 editions) Hong Kong dollar images; 10 white light images and infrared images, normalized to a size of 200*100.
[0104] 1. Construct the given normalized banknote white light image and infrared image as a training sample set S, where images of different versions of Hong Kong dollars are marked as 1 to 12 images of 12 different categories.
[0105] 2. Extract the gray level co-occurrence matrix texture features of the Hong Kong dollar image according to the formula. Calculate and obtain five texture parameters of Hong Kong dollar sample image: entropy (ENT), inverse difference moment (IDM), energy (angular second moment, ASM), contrast (CCW) and correlation coefficient (COR).
[0106] 3. Use the BP neural network to classify the texture fea...
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