• Journal of the Korea Society of Computer and Information
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• v.8 no.3
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• pp.94-99
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• 2003

In this paper, a rotation invariant fingerprint identification system is implemented using the circular harmonic filter and phase only correlator. We extracted the phase component from input fingerprint image and correlate it with the circular harmonic filter of the reference fingerprint image by POC. The input image is obtained using a prism operating in the internal full reflection mode. Then the input image is transformed to two dimensional Fourier spectrum in optical way and the phase component is extracted using a digital system from the spectrum. Because composed of the optical system and digital algorithm, the proposed system has the advantages of the two technologies such as realtime parallel processing property of the optics and the flexibility of the digital system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9C
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• pp.860-867
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• 2003

In this paper, an efficient core point detection method using orientation pattern labeling is proposed in fingerprint image. The core point, which is one of the singular points in fingerprint image, is used as the reference point in the most fingerprint recognizing system. Therefore, the detection of the core point is the most essential step of the fingerprint recognizing system, it can affect in the whole system performance. The proposed method could detect the position of the core point by applying the labeling method for the directional pattern which is come from the distribution of the ridges in fingerprint image and applying detailed algorithms for the decision of the core point's position. The simulation result of proposed method is better than the result of Poincare index method and the sine map method in executing time and detecting rate. Especially, the Poincare index method can't detect the core point in the detection of the arch type and the sine map method takes too much times for executing. But the proposed method can overcome these problems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.3
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• pp.217-226
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• 2003

A novel fingerprint ridge feature extraction using sequential labeling of thinned fingerprint image is proposed, which is invariant to position translation, scaling, and rotation. the proposed algorithm labels ridges of thinned fingerprint image sequentially using vertical line that goes through fingerprint core point. Then, we extract a feature from each labeled ridge and the extraction process is based on the type fo the ridge and a minutiae ridge angle in the ridge. The feature extracted through this process enables us to find out the kind of various minutiae and minutiae angle. As a result of the experiment using two thinned fingerprint images, we finally confirm that proposed algorithm is not related to position translation, scaling, and rotation.

• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.63-68
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• 2003

Almost the system are usually taken by means of shapes and positions of ridge's end-points and bifurcation in the fingerprint recognition. but we studied about recognition of polluted fingerprint by chain code ridges. the results and sequence of processing are summarized as follows. (1)Capture several kinds of polluted fingerprint image. (2)Preprocessing(median filtering for removing noises, local and global histogram equalization, dilation and erosion, thinning and remove pseudo image), (3)Rebuild ridge line after Least Square Processing, (4)Compute distribution of chain code vector, (5)The results are almost same values of each vector of preprocessed fingerprint images. From the results, we can surmised more successful fingerprints recognition system in combination with other system by singular points

• Journal of Industrial Technology
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• v.19
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• pp.403-408
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• 1999

An efficient method is developed for classifying fingerprint data based on 2-D discrete wavelet transform. Fingerprint data is first converted to a binary image. Then a multi-level 2-D wavelet transform is performed. Vertical and horizontal subbands of the transformed data show typical energy distribution patterns relevant to the fingerprint categories. The proposed method with moderate level of wavelet transform is successful in classifying fingerprints into 5 different types. Finer classification is possible by higher frequency subbands and closer analysis of energy distribution.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.231-232
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• 2007

This paper introduce a new touchless fingerprint sensor. Two mirrors are used to capture the side fingerprint images which cannot detectable using a single camera. We also propose the techniques which can solve the image contrast, nonuniform illumination, DOF(Depth of Field) problems. This new sensor leads to bringing new challenges in the field of fingerprint recognition.

• ETRI Journal
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• v.28 no.4
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• pp.444-452
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• 2006

Biometric-based authentication can provide a strong security guarantee of the identity of users. However, the security of biometric data is particularly important as any compromise of the biometric data will be permanent. In this paper, we propose a secure and efficient protocol to transmit fingerprint images from a fingerprint sensor to a client by exploiting the characteristics of the fingerprint images. Because the fingerprint sensor is computationally limited, a standard encryption algorithm may not be applied to the full fingerprint images in real-time to guarantee the integrity and confidentiality of the fingerprint images transmitted. To reduce the computational workload on the resource-constrained sensor, we apply the encryption algorithm to a nonce for integrity and to a specific bitplane of each pixel of the fingerprint image for confidentiality. Experimental results show that the integrity and confidentiality of the fingerprint images can be guaranteed without any leakage of the fingerprint ridge information and can be completed in real-time on embedded processors.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2816-2822
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• 1999

In this paper, a fast thinning method for fingerprint image by separating end and bifurcation region is proposed. To detect feature points in automatic fingerprint identification system, thinning of fingerprint is essential. The end and bifurcation regions in ridge line are separated by means of run-length coding, and parallel thinning method is applied to the separated regions. The rest parts except the end and bifurcation regions are processed by connecting center points of each run. The performance of the proposed method has been evaluated by CPU processing time and thinness measurement. By the experimental results, the proposed method is fast and has high thinness value.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.89-98
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• 2005

Fingerprint segmentation and ridge orientation estimation algorithms with images from a mobile camera are proposed. The fingerprint images from a mobile camera are quite different from those from conventional sensor, called touch based sensor such as optical, capacitive, and thermal. For example, the images from a mobile camera are colored and the backgrounds or non-finger regions are very erratic depending on how the image capture time and place. Also the contrast between ridge and valley of a mobile camera image are lower than that of touch based sensor image. To segment fingerprint region, we first detect the initial region using color information and texture information. The LUT (Look Up Table) is used to model the color distribution of fingerprint images using manually segmented images and frequency information is extracted to discriminate between in focused fingerprint regions and out of focused background regions. With the detected initial region, the region growing algerian is executed to segment final fingerprint region. In fingerprint orientation estimation, the problem of gradient based method is very sensitive to outlier that occurred by scar and camera noise. To solve this problem, we propose a robust regression method that removes the outlier iteratively and effectively. In the experiments, we evaluated the result of the proposed fingerprint segmentation algerian using 600 manually segmented images and compared the orientation algorithms in terms of recognition accuracy.

• Analytical Science and Technology
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• v.29 no.6
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• pp.283-292
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• 2016

Conventional fingerprint powders used during crime scene investigations pose potential health hazards. Thus, multiple natural replacement powders, including squid ink powder, indigo and rice powder were used to develop (visualize) latent fingerprints on non-porous surfaces (e.g., glass, plastic and tile). Fingerprints developed using the natural powders were compared using the Automatic Fingerprint Identification System (AFIS) with those developed with traditional black powder. The peak areas of ridges were also compared using densitometric image analyses. Collectively, objective and quantitative evaluation methods were developed. The effectiveness of natural powders varied depending on the surface but, in general, squid ink powder performed well on most surfaces. Indigo powder performed well on tile surfaces, while rice powder performed well on glass surfaces. Plastic was the most difficult surface from which to develop fingerprints. Image analysis using Field Emission Scanning Electron Microscopy (SEM) demonstrated the importance of the size and shape of natural powder particles to properly adhere to the ridges. Although densitometric image analyses did not correlate the number of minutiae and ridge peak areas, an unbiased, objective evaluation method would be possible using image analyses with a reference image. Additional experimentation will yield safe and cost-effective natural powders with which adequate fingerprint development can be performed.