• Journal of Information Technology Services
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• v.7 no.4
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• pp.139-149
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• 2008

We propose expert system for restoration the original character form of ancient relics based on image processing and computer graphics. Letters engraved in relief like relics and intaglio like curved tombstones and letters engraved in plane or curved part of cultural asset may have been broken by a lot of rubbed copy, a long time and tide. In this paper, we suggest a new method for extracting and recovering the broken letters of cultural asset into an original form by using Z-map, morphological filter, and high frequency filter. Based on the suggested method. we develop the character recovering system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.177-182
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• 2010

Research on recovering original images from captions has been widely done in a reusability point of view. In usual, dynamic images imported from foreign countries often have captions of foreign languages, so it is necessary to translate them into one's language. For the natural exchange of captions without loss of original images, recovering the images corresponding to captions is necessary. However, though recovering original images is very important, systematic analysis on the characteristics of captions has not been done yet. Therefore, in this paper, we first survey the classification methods of TV programs at academic worlds, broadcasting stations, and broadcasting organizations, and then analyses the frequency of captions, importance of caption contents, and necessity of recovering according to their types. Also, we analyze the characteristics of captions which are significantly recognized to be necessary to recover, and use them as recovering information.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.767-774
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• 2002

Conventional research on image restoration has focused on restoring degraded images resulting from image formation, storage and communication, mainly in the signal processing field. Related research on recovering original image information of caption regions includes a method using BMA(block matching algorithm). The method has problem with frequent incorrect matching and propagating the errors by incorrect matching. Moreover, it is impossible to recover the frames between two scene changes when scene changes occur more than twice. In this paper, we propose a method for recovering original images using EBMA(Extended Block Matching Algorithm) and a region compensation method. To use it in original image recovery, the method extracts a priori knowledge such as information about scene changes, camera motion and caption regions. The method decides the direction of recovery using the extracted caption information(the start and end frames of a caption) and scene change information. According to the direction of recovery, the recovery is performed in units of character components using EBMA and the region compensation method. Experimental results show that EBMA results in good recovery regardless of the speed of moving object and complexity of background in video. The region compensation method recovered original images successfully, when there is no information about the original image to refer to.

• KSCI Review
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• v.14 no.2
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• pp.141-146
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• 2006

In this paper, we propose a new algorithm for recovering the broken letters of relics into an original form by using Z-map and image processing. The letters of relics may have been broken by a lot of rubbed copy and a long time and tide. They need to be restored. But the manual reconstruction is a very tedious and laborious task. Thus, it is necessary to automate the restoration process. This paper presents a realistic algorithm with an application to Tripitaka Koreana by using Z-map and morphological filter.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.113-122
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• 2000

It is sometimes necessary to remove the captions and recover original images from video images already broadcast, When the number of images requiring such recovery is small, manual processing is possible, but as the number grows it would be very difficult to do it manually. Therefore, a method for recovering original image for the caption areas in needed. Traditional research on image restoration has focused on restoring blurred images to sharp images using frequency filtering or video coding for transferring video images. This paper proposes a method for automatically recovering original image using BMA(Block Matching Algorithm). We extract information on caption regions and scene change that is used as a prior-knowledge for recovering original image. From the result of caption information detection, we know the start and end frames of captions in video and the character areas in the caption regions. The direction for the recovery is decided using information on the scene change and caption region(the start and end frame for captions). According to the direction, we recover the original image by performing block matching for character components in extracted caption region. Experimental results show that the case of stationary images with little camera or object motion is well recovered. We see that the case of images with motion in complex background is also recovered.

• Journal of the Korea Society of Computer and Information
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• v.10 no.2 s.34
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• pp.97-104
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• 2005

Caption texts frequently inserted in a manufactured video image for helping an understanding of the TV audience. In the movies. replacement of the caption texts can be achieved without any loss of an original image, because the caption texts have their own track in the films. To replace the caption texts in early methods. the new texts have been inserted the caption area in the video images, which is filled a certain color for removing established caption texts. However, the use of these methods could be lost the original images in the caption area, so it is a Problematic method to the TV audience. In this Paper, we propose a new method for replacing the caption text after recovering original image in the caption area. In the experiments. the results in the complex images show some distortion after recovering original images, but most results show a good caption text with the recovered image. As such, this new method is effectively demonstrated to replace the caption texts in video images.

• Journal of the Optical Society of Korea
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• v.19 no.1
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• pp.102-111
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• 2015

This paper proposes an algorithm for recovering the colors of objects from multiple near-infrared (near-IR) images. The International Commission on Illumination (CIE) color coordinates of objects are recovered from a series of gray images captured under multiple spectral near-IR illuminations using polynomial regression. The feasibility of the proposed algorithm is tested experimentally by using 24 color patches of the Color Rendition Chart. The experimental apparatus is composed of a monochrome digital camera without an IR cut-off filter and a custom-designed LED illuminator emitting multiple spectral near-IR illuminations, with peak wavelengths near the red edge of the visible band, namely at 700, 740, 780, and 860 nm. The average color difference between the original and the recovered colors for all 24 patches was found to be 11.1. However, if some particular patches with high value are disregarded, the average color difference is reduced to 4.2, and this value is within the acceptability tolerance for complex image on the display.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.574-575
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• 2021

Re-manufacturing is the process of recovering the function and performance of the original product through a re-assembly process such as a new product assembly process after reprocessing by recovering used products or parts that are in the disposal stage at the end of their lifespan. One of the manufacturing methods. The remanufacturing industry is important not only in terms of environmental protection, but also in terms of economics. The success or failure of the industry as a whole depends on trust in products and price competitiveness. Image processing systems are used to reduce labor costs and improve product reliability in the product manufacturing process. In this study, foreign substances and defects that are difficult to identify with the human eye are detected by using the pre-processing step of determining whether to recycle the drum and image processing immediately before shipment after regenerating the drum to regenerate the waste drum.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.269-277
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• 2006

We propose a new expert system for recovering the broken fragments of relics into an original form using computer graphics and image processing. This paper presents a system with an application to tombstones objects of flat plane with letters carved in for assembling the fragments by placing their respective fragments in the right position. The matching process contains three sub-processes: aligning the front and letters of an object, identifying the matching directions, and determining the detailed matching positions. We apply least squares fitting, vector inner product, and geometric and RGB errors to the matching process. It turned out that 2-D translations via fragments-alignment enable us to save the computational load significantly. Based on experimental results from the damaged cultural fragments, the performance of the proposed method is illustrated.

• International Journal of Contents
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• v.12 no.3
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• pp.22-28
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• 2016

Tensor with missing or incomplete values is a ubiquitous problem in various fields such as biomedical signal processing, image processing, and social network analysis. In this paper, we considered how to reconstruct a dataset with missing values by using tensor form which is called tensor completion process. We applied Tucker factorization to solve tensor completion which was built base on optimization problem. We formulated the optimization objective function using components of Tucker model after decomposing. The weighted least square matric contained only known values of the tensor with low rank in its modes. A first order optimization method, namely Nonlinear Conjugated Gradient, was applied to solve the optimization problem. We demonstrated the effectiveness of the proposed method in EEG signals with about 70% missing entries compared to other algorithms. The relative error was proposed to compare the difference between original tensor and the process output.