• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.1025-1034
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• 2009

In steel making production line, steel slabs are given a unique identification number. This identification number, Slab management number(SMN), gives information about the use of the slab. Identification of SMN has been done by humans for several years, but this is expensive and not accurate and it has been a heavy burden on the workers. Consequently, to improve efficiency, automatic recognition system is desirable. Generally, a recognition system consists of text localization, text extraction, character segmentation, and character recognition. For exact SMN identification, all the stage of the recognition system must be successful. In particular, the text localization is great important stage and difficult to process. However, because of many text-like patterns in a complex background and high fuzziness between the slab and background, directly extracting text region is difficult to process. If the slab region including SMN can be detected precisely, text localization algorithm will be able to be developed on the more simple method and the processing time of the overall recognition system will be reduced. This paper describes about the slab region localization using SIFT(Scale Invariant Feature Transform) features in the image. First, SIFT algorithm is applied the captured background and slab image, then features of two images are matched by Nearest Neighbor(NN) algorithm. However, correct matching rate can be low when two images are matched. Thus, to remove incorrect match between the features of two images, geometric locations of the matched two feature points are used. Finally, search rectangle method is performed in correct matching features, and then the top boundary and side boundaries of the slab region are determined. For this processes, we can reduce search region for extraction of SMN from the slab image. Most cases, to extract text region, search region is heuristically fixed [1][2]. However, the proposed algorithm is more analytic than other algorithms, because the search region is not fixed and the slab region is searched in the whole image. Experimental results show that the proposed algorithm has a good performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.809-812
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• 2006

This paper describes about the vision system, which was developed for the recognition of material management characters in the slab processing line. The material management characters, which are marked at the surface of a slab, are recognized by real time processing before slab moves to the next hot strip line. The vision system for the character recognition include that CCD camera system which acquire slab image, image transmission system which transmit captured image to the long distance, I/O devices for the interface with peripheral control system. We have installed vision system to the slab processing line and tested. Through the testing, we have checked durability, reliability and recognition rate of our system. In the results, we have confirmed that our system have good performance and higher recognition ability.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.1
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• pp.95-100
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• 2007

In the steel & iron processing line, some characters are marked for the material management in the surface of material. This paper describes about the developed results of vision system for the recognition of material management characters, which was included in the slab image. Our vision system for the character recognition includes that CCD camera system which acquire slab image, optical transmission system which transmit captured image to the long distance, input and output system for the interface with existing system and monitoring system for the checking of recognition results. We have installed our vision system at the continuous casting line and tested. Also, we have performed inspection of durability, reliability and recognition rate. Through the testing, we have confirmed that our system have high recognition rate, 97.4%.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.806-816
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• 2009

Character recognition system consists of four step; text localization, text segmentation, character segmentation, and recognition. The character segmentation is very important and difficult because of noise, illumination, and so on. For high recognition rates of the system, it is necessary to take good performance of character segmentation algorithm. Many algorithms for character segmentation have been developed up to now, and many people have been recently making researches in segmentation of touching or overlapping character. Most of algorithms cannot apply to the text regions of management number marked on the slab in steel image, because the text regions are irregular such as touching character by strong illumination and by trouble of nozzle in marking machine, and loss of character. It is difficult to gain high success rate in various cases. This paper describes a new algorithm of character segmentation to recognize slab management number marked on the slab in the steel image. It is very important that pre-processing step is to convert gray image to binary image without loss of character and touching character. In this binary image, non-touching characters are simply separated by using vertical projection profile. For separating touching characters, after we use combined profile to find candidate points of boundary, decide real character boundary by using method based on recognition. In recognition step, we remove noise of character images, then recognize respective character images. In this paper, the proposed algorithm is effective for character segmentation and recognition of various text regions on the slab in steel image.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.986-989
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• 2003

In the steel production line, the molten metal of a furnace is transformed into slab material and then move to the hot strip line, This paper describe about the real time recognition system of material management number, which is marked at the surface of a slab in the steel production line. This recognition processing should be performed before the slab is moved to the hot strip line. This system include following recognition steps. First, we remove noise from the captured slab image by use pre-filter. Second, we extract rough area, which is include slab number and then, we extract individual number area. Finally, we recognize material management number by use KLT(Karhunen-Loeve transform) algorithm. We applied our system to the real slave image, which was captured in the process line. In the results, we recognized slave number to the 94% accuracy.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.3_4
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• pp.195-203
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• 2004

VolumePro is a real-time volume rendering hardware for consumer PCs. However it cannot be used for the applications requiring perspective projection such as virtual endoscopy since it provides only orthographic projection. Several methods have been presented to approximate perspective projection by decomposing a volume into slabs and applying successive parallel projection to thou. But it takes a lot of time since the entire region of every slab should be processed, which does not contribute to final image. In this paper, we propose an efficient perspective projection method that makes the use of several sub-volumes with cropping feature of VolumePro. It reduces the rendering time in comparison to slab-based method without image quality deterioration since it processes only the parts contained in the view frustum.

• Journal of the Optical Society of Korea
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• v.18 no.6
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• pp.679-684
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• 2014

Enhanced analysis is performed to design a wedge projection system with a slab structure that increases the projected image size. The specification values of the system such as the length of the slab structure and the imaging region are calculated and investigated using an optical simulation tool. We also propose a split imaging region method to represent a large tiled scene using the thin wedge waveguide structure. Experiments are performed to verify the feasibility of the proposed method.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1819-1820
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• 2008

Steel slabs are marked with slab management numbers (SMNs). To increase efficiency, automated identification of SMNs from digital images is desirable. Automatic extraction of SMNs is a prerequisite for automatic character segmentation and recognition. The images include complex background, and the position of the text region of the slabs is variable. This paper describes an pre-processing algorithm for detection of slab information using robust feature points extraction. Using SIFT(Scale Invariant Feature Transform) algorithm, we can reduce the search region for extraction of SMNs from the slab image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.545-550
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• 2011

This paper introduces an Integrated Vision System that enables us to detect the image of slabs and coils and get the complete three dimensional location data without any other obstacles in the field of unmanned-crane automation system. Existing vision system research tends to be easily influenced by the environment of the work place and therefore cannot give the exact location information. To overcome these weaknesses, this paper suggests laser scanners should be combined with a CCD camera named Integrated Vision System. The suggested system is expected to help improve the unmanned-crane automation system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1897-1902
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• 2008

In computer vision analysis of detecting concrete slab surface cracks, there are many difficulties to overcome. Target images often have defamations due to the light condition and other external environment. Another difficulties in detecting concrete crack image is that there is no clear distinction in intensity between the crack and the surface since the surface is often irregular. In this paper, we apply ART2 based quantization in order to classify target concrete slab surface images into several areas with respect to the light intensity. From those quantized areas, we investigate the distribution of real cracks and noises. Then, we extract candidate crack areas after applying noise removal process to areas which have be th oracle and noises. Finally, crack areas are recognized by using morphological features of cracks from such candidate areas. In experiment with real world concrete slab structure images, our algorithm has advantage in recognizing accuracy of cracks to other algorithms especially in relatively brighter areas of concrete surface.