Study On Image Acquisition And Recognition For Protuberant Character On Label Based On Moiré Technology

The label is the basic signs that carry amounts of important information of product. The recognition of this information is of great significance for information management during the production, transportation and sales.The contents on the label are classified as the fixed and dynamic data. The former are usually printed on the label surface in advance, and the latter which are protuberant characters on the label are pressed by a protuberant mould, so that the protuberant characters are permanent and have a function of anti-counterfeiting.As to the abuse of checking and recognition completed by man after the character pressed and as to the information recorded of product by producer, subject of automatic recognition protuberant character was proposed. Stressing to improve original image quality, we presented a way of image acquisition based on Moire technology. Combining the characteristics of character image with the optical character recognition, we studied image acquisition, pre-processing of character image, feature extraction and classification recognition methods of character.We researched the features of Moire fringes formed in different cases and the influencing factors of Moire fringes formed by sine gratings and rectangle gratings. The research is of great theoretical and practical value to design of an optical system based on Moire technology.After analyzing Moire fringes, we gave a theoretical analysis of image acquisition based on shadow Moire, designed grating sensors and experimental devices, and analyzed the experimental results. Contrasted with the conventional acquired images, the images obtained by shadow Moire have higher quality.As the threshold and the image edge are the key information during the image processing, we proposed an adaptive binarized method through combining the optimal global threshold with the local threshold based on edge detection. The basic principle and the algorithm of the adaptive method are given.The circular projection transformation is a method of feature extraction that has scale, rotation, and translation invariance. It takes centroid as apex transform Descartes coordinates into the polar coordinate, and calculate the sum of pixel value on the same radius. It changes two-dimensional character image into one-dimensional circular projection curve. A quick calculation of circular projection curve is put forward through indexing the table of pseudo digit circle.The curve of circular projection can be decomposed by use of the multi-resolution analysis of wavelet. The approximate signals as the feature of character recognition are extracted in the scale space, and the detailed signals are obtained in the wavelet space. Finally, the dimension of approximate signal is further reduced through the discrete cosine transformation to realize quick character recognition.Being based on the feature extraction of the circular projection, we simulated the number set of the pressed characters on the label and compared with other classifiers, such as template matching, neural networks. The experimental results show that this method has a high recognition rate and practicability for the recognition of small character sets.This research work was supported by a grant of Programs Foundation of Ministry of Education of China.