• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2275-2278
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• 2003

In this paper, we propose a visual inspection algorithm to detect can print-errors by using multi-camera and image valuing algorithm. The features of the algorithm are to use four cameras that are arranged with 90$^{\circ}$ between each other and to adopt a synthesized image model which represents whole surface of a can. Using the model, detection process is straight forward, namely it is comparing a partial region of the can to a specific region of the model where is previously marked.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2249-2251
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• 1998

This paper presents a lip print recognition by the pattern kernels for a personal identification. A lip print recognition is developed less than the other physical attribute that is a fingerprint, a voice pattern, a retinal blood-vessel pattern, or a facial recognition. A new method by the pattern kernels is pro for a lip print recognition. The pattern kerne function consisted of some local lip print p masks. This function identifies the lip print known person or an unknown person. The results show that the proposed algorithm the pattern kernels can the efficiently realized.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.64-69
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• 1998

This paper presents a lip print recognition by the pattern kernels for a personal identification. A lip print recognition is developed less than the other physical attributes of a fingerprint, a voice pattern, a retinal blood/vessel pattern, or a facial recognition. A new method is proposed to recognize a lip print bi the pattern kernels. The pattern kernels are a function consisted of some local lip print pattern masks. This function converts the information on a lip print into the digital data. The recognition in the multi-resolution system is more reliable than recognition in the single-resolution system. The results show that the proposed algorithm by the multi-resolution architecture can be efficiently realized.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07b
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• pp.1163-1167
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• 2003

As a PD classification method, statistical distribution parameters have been used during several ten years. And this parameters are recently finger print method, NN(Neural Network) and etc. So in this paper we studied finger print method and NN with BP(Back propagation) learning algorithm using the statistical distribution parameter, and compared with two method as classification method. As a result of comparison, classification of NN is more good result than Finger print method in respect to calculation speed, visible effect and simplicity. So, NN has more advantage as a tool for PD classification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.131-146
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• 2021

Multimodal biometric-based recognition has been an active topic because of its higher convenience in recent years. Due to high user convenience of finger, finger-based personal identification has been widely used in practice. Hence, taking Finger-Print (FP), Finger-Vein (FV) and Finger-Knuckle-Print (FKP) as the ingredients of characteristic, their feature representation were helpful for improving the universality and reliability in identification. To usefully fuse the multimodal finger-features together, a new robust representation algorithm was proposed based on hierarchical model. Firstly, to obtain more robust features, the feature maps were obtained by Gabor magnitude feature coding and then described by Local Binary Pattern (LBP). Secondly, the LGBP-based feature maps were processed hierarchically in bottom-up mode by variable rectangle and circle granules, respectively. Finally, the intension of each granule was represented by Local-invariant Gray Features (LGFs) and called Hierarchical Local-Gabor-based Gray Invariant Features (HLGGIFs). Experiment results revealed that the proposed algorithm is capable of improving rotation variation of finger-pose, and achieving lower Equal Error Rate (EER) in our homemade database.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.47-48
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• 2010

• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1510-1519
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• 2005

We proposed a digital watermarking method that it is possible to identify the copyright because the watermark is detected in the first print-scan and to protect a forgery because the watermark is not detected in the second print-scan. The proposed algorithm uses LPM and DFT transform for the robustness to the distortion of pixel value and geometrical distortion. This methods could improve watermark detection performance and image quality by selecting maximum sampling radius in LPM transform. After analyzing the characteristics of print-scan process, we inserted the watermark in the experimentally selected frequency bands that survives robustly to the first print-scan and is not detected in the second print-scan, using the characteristic of relatively large distortion in high frequency bands of DFT As the experimental result, the original proof is possible because average similarity degree 5.13 is more than the critical value 4.0 in the first print-scan. And the detection of forgery image is also possible because average similarity degree 2.76 is less than the critical value 4.0 in the second print-scan.

• Journal of Korea Multimedia Society
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• v.16 no.9
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• pp.1057-1066
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• 2013

Personal verification using finger-knuckle-print(FKP) uses lines and creases at the finger-knuckle area, so the orientation information of texture is an important feature. In this paper, we propose an effective FKP verification method which extracts keypoints using SIFT algorithm and matches the keypoints by vector similarity. The vector is defined as a direction vector which connects a keypoint extracted from a query image and a corresponding keypoint extracted from a reference image. Since the direction vector is created by a pair of local keypoints, the direction vector itself represents only a local feature. However, it has an advantage of expanding a local feature to a global feature by comparing the vector similarity among vectors in two images. The experimental results show that the proposed method is superior to the previous methods based on orientation codes.

• IE interfaces
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• v.22 no.1
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• pp.85-94
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• 2009

Nowadays, most of the major manufacturing companies prepare their manufacturing schedule using package based solutions. Even though the accuracy of the detail scheduling result is high at implementation, however, it is low during maintenance period. The main cause of low accuracy during maintenance period is due to difficulties in maintaining the accurate level of master data. In this paper, we propose to easily maintain setup time, which is one of the most important factors required in master data to achieve good scheduling result, after changing job. This paper is mainly focused on how to deduce the factors that influence the setup time in a roll-based manufacturing field with print operations. For this purpose, we employed rule based algorithm and applied for deciding setup time for the existing product items. Likewise, it can be applied to new items without any complex setup procedures, and, finally, it displays the result of the real setup-time and calculated setup-time.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.134-136
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• 2003

This paper proposes an algorithm for fingerprint identification using phase only correlation. This algorithm uses the phase of fast Fourier transform and correlation function to calculate the similarity. The algorithm gives very clear result for identification because it shows only one conspicuous sharp peak for the same person's fingerprint. Further, it shows good results even for the finger print images which are printed not clearly and does not need to preprocess the images. It also shows good results for parallel displacement of fingerprint. The experiment result shows the effectiveness of the proposed algorithm.