Study On The Key Points Of The Image Acquisition And Processing For Characters Pressed On Labels

Characters formed on the surface of objects by machining method are widely used in industrial products. These characters are three-dimensional characters and they have the same color as the background. It is this characteristic that makes it difficult to use the existing research achievements of the traditional optical character recognition(OCR) to recognize them. Accordingly, recognition of such characters becomes a new hot spot in optical character recognition research field. Recently, with the development of the information technology, auto-recognition systems for pressed characters become a necessary requirement for Product Information Management. Supported by Doctoral Fund of Ministry of Education of China, the research carried out in this thesis is as followings.A machine vision image acquisition system for characters pressed on labels is designed. The quality of images acquired is a main factor to affect the performance of the pressed character recognition system. In order to improve the quality of the label image, the components of the machine vision system are introduced and their performance is analyzed. Illumination is vital in machine vision applications for providing contrast so that the camera can see the image clearly. Effect of the illumination on the label images is analyzed. To be effective, the illumination needs to provide an adequate amount of uniform light and be from the correct angle, so as to get enough information of the pressed characters from the label image. Effect of the several illumination schemes for machine vision imaging systems of label is studied. Also, the reflective properties of the label are analyzed. Based on LED lighting, an image acquisition system for label is established. Experiments on labels with different kinds of materials and layouts are carried out and the results prove that the low-angle LED lighting is the best illumination scheme for the characters pressed on label.Illumination preprocessing methods for label images are studied. According to the characteristics of the label images, several illumination preprocessing methods are applied on them. In order to choose a best illumination preprocessing method for label, a comparison scheme is designed. Both the theoretical analysis and the experiment results prove that the homomorphic filter can be reliably used for illumination preprocessing of label images.A novel segmentation method for characters pressed on label based on layered images is presented. Automatic segmentation methods for segmenting the characters from the label image are studied systematically. According to the characteristics of the label image, a segmentation method based on layered images is presented. The algorithm classified the label image into three planes: the brightest plane, the darkest plane and the middle plane. The printed text on the label is extracted from the adaptively binary image of the darkest plane. Then, the block of printed text is defined based on connect components analysis. Finally, by removing the block of the printed text from the original image, the pressed characters are picked up successfully. Experiments are carried out with a large number of label images. Experiment results show that the proposed segmentation method can be reliably used in the label images.Image quality assessment and restoration algorithms for the pressed characters are studied. The quality of image acquired is a key factor to affect the accuracy of character recognition system. Algorithms for estimating the quality of any given images can be used to automatically determine improvement made by adaptive image-restoration algorithms. In order to estimate the quality of the image, five quality measures are introduced. That is, small speckle factor, white speckle factor, broken character factor, touching character factor and character-height, width and location factor. Based on the information provided by the quality measures, a quantitative grade can be given to the label image for its quality estimation. Several image-restoration algorithms are introduced to improve the label image. Also, based on the quality measures, characters with different qualities can be segmented from a label image, which is helpful to adaptly select the image processing algorithm for characters with specific quality. Recognition the pressed characters with their direction feature extracted by Gabor filters. A novel feature extraction method for raised or indented characters pressed on a label using Gabor transform based on the gray image is presented. A set of Gabor filters is designed according to the characteristics of the pressed characters. These filters are used to break down a gray image of a character into four directional feature sub-images to get the local Gabor features. Based on these local features, an invariant feature space is established. Experiments are carried out with a large number of raised or indented character images. Experiment results show that the proposed invariant Gabor features have great separate capability and have great robust to rotation, scale, translation invariance and are also insensitive to illumination conditions and noise changes. It is proved that Gabor transform can be reliably used for extracting the feature of low quality character in image processing.This work is supported by Doctoral Fund of Ministry of Education of China.