For the requirement of identification and trace of steel billet in the procedure of manufacture and management, the ends of
steel billets are all printed a series of characters. So, each end of steel billet must be tracked and recognized automatically
before they are imported to furnace. Owing to the effect of the bad-imaging environment, there are a lot of difficulties in
recognizing characters at ends of steel billet. So, the real-time automatic recognition of characters at ends of steel billet is
different from the recognition of the license plates. For the former methods dissatisfied with practical demands, an
identification method using features of character structures is introduced by this paper, which greatly lowers error rate and
rejection rate effectively.
For the requirement of identification and trace of steel billet in the procedure of manufacture and management, the ends of
steel billets are all printed a series of characters. So, each end of steel billet must be tracked and recognized automatically
before they are imported to furnace. Owing to the effect of the bad-imaging environment, there are a lot of difficulties in
recognizing characters at ends of steel billet. So, the real-time automatic recognition of characters at ends of steel billet is
different from the recognition of the license plates. For the former methods dissatisfied with practical demands, an
identification method using features of character structures is introduced by this paper, which greatly lowers error rate and
rejection rate effectively.
COG (chip on glass) bonding is widely used in LCD industry. The alignment of marks in COG bonding needs high
precision and reliability. It is of utmost importance to find two marks in COG fast and exactly. Its key technique is to use
the advanced optical system to get the two-marked positions of chip on the glass and to use the PLC procedure control
to complete the automatic alignment A series of experiments are performed to test the algorithms proposed, which show
that the fast alignment of marks in COG bonding based on multi-resolution is both rational and highly effective.
Counting of different classes of white blood cells in bone marrow smears can give pathologists valuable information regarding various cancers. But it is tedious to manually locate, identify, and count these classes of cells, even by skilled hands. This paper presents a novel approach for automatic detection of White Blood Cells in bone marrow microscopic images. Different from traditional color imaging method, we use multispectral imaging techniques for image acquisition. The combination of conventional digital imaging with spectroscopy can provide us with additional useful spectral information in common pathological samples. With our spectral calibration method, device-independent images can be acquired, which is almost impossible in conventional color imaging method. A novel segmentation algorithm using spectral operation is presented in this paper. Experiments show that the segmentation is robust, precise, with low computational cost and insensitive to smear staining and illumination condition. Once the nuclei and cytoplasm have been segmented, more than a hundred of features are extracted under the direction of a pathologist, including shape features, textural features and spectral ratio features. In pattern recognition, a maximum likelihood classifier (MLC) is implemented in a hierarchical tree. The classification results are also discussed. This paper is focused on image acquisition and segmentation.
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