Kil-Houm Park

Robust digital image watermarking method against geometrical attacks

This paper proposes a new image watermarking scheme which is robust to RST attacks with cropping by improving Fourier-Mellin transform based watermarking (FMW). The proposed scheme reorders and modifies function blocks of FMW for improvement of realization and performance. Unlike FMW, our method uses log-polar map (LPM) in the spatial domain for scaling invariance, while translation invariance is provided by the use of an invariant centroid (IC) as the origin of LPM. IC is a gravity center of a central area on gray scale image that is invariant although an image is attacked by RST. For this, its calculation method is proposed. Also since LPM includes the property which transforms rotation of Cartesian coordinates system into a cyclic shift, 2-D DFT is performed on the LPM image and the magnitude spectrum extracted to provide a domain that is rotation invariant. The resulting domain, which is invariant to RST, is then used as the watermark-embedding domain. Furthermore, to prevent the watermarked image from degrading due to the coordinate system conversion, only LPM image of watermark signal is inverse mapped to Cartesian coordinates and add to the original image. Experimental results demonstrate that the proposed scheme is robust to RST attacks.

Singular point detection by shape analysis of directional fields in fingerprints

This paper presents a new fingerprint singular point detection method that is type-distinguishable and applicable to various fingerprint images regardless of their resolutions. The proposed method detects singular points by analyzing the shapes of the local directional fields of a fingerprint image. Using the predefined rules, all types of singular points (upper core, lower core, and delta points) can be extracted accurately and delineated in terms of the type of singular points. In case of arch-type fingerprints there exists no singular point, but reference points for arch-type fingerprints are required to be detected for registration. Therefore, we propose a new reference point detection method for arch-type fingerprints as well. The result of the experiments on the two public databases (FVC2000 2a, FVC2002 2a) with different resolutions demonstrates that the proposed method has high accuracy in locating each types of singular points and detecting the reference points of arch-type fingerprints without regard to their image resolutions.

Iris-based personal authentication using a normalized directional energy feature

In iris-based biometric systems, iris images acquired by a video or CCD camera generally have a lot of contrast or brightness differences in an image or between images due to the different extent of camera focusing or illumination conditions. To extract the discriminatory iris features robust to such differences, this paper presents a new normalization scheme of the directional energy that will be used as the iris feature. The proposed method first performs band-pass filtering on the input iris image to reduce the effect of high frequency noise and DC energy difference, then decomposes the image into several directional subband outputs using a directional filter bank (DFB). The directional energy values of the iris pattern are extracted from the decomposed subband outputs on a block-by-block basis and then are normalized with respect to the total block energy. Matching is performed by finding the Euclidean distance between the input and enrolled template feature vector. Experimental results show that the proposed method is robust to changes in illumination or contrast and the overall feature extraction and matching procedures are effective.

Directional filter bank-based fingerprint feature extraction and matching

The paper presents a new filter bank-based fingerprint feature extraction and matching method without needing to detect minutiae. The proposed method decomposes a fingerprint image into eight directional subband outputs using a directional filter bank (DFB) and then obtains directional energy distributions for each block from the decomposed subband outputs. Only dominant directional energy components are employed as elements of the input feature vector, which serves to reduce noise and improve efficiency. For the rotational alignment, additional input feature vectors in which various rotations are considered are extracted, and these input feature vectors are compared with the enrolled template feature vector. The proposed method significantly reduces the memory cost and processing time associated with verification, primarily because of the efficient DFB structure and the exploitation of directional specific information. Experimental results validate the effectiveness of the proposed method in extracting fingerprint features and achieving good performance.

A New Reference Point Detection Algorithm Based on Orientation Pattern Labeling in Fingerprint Images

Most fingerprint-based biometric systems establish a reference point in a fingerprint, then extract features based on this reference point. As such, the consistency and accuracy of the reference point location considerably affects the overall system performance. Accordingly, this paper presents an accurate and consistent reference point detection algorithm based on orientation pattern labeling. Experimental results demonstrate that the proposed method can produce a better performance in terms of accuracy and speed than Poincare index or sine map-based methods.

Mobile IP and WLAN with AAA authentication protocol using identity-based cryptography

The Mobile IP application of AAA (Diameter protocol) provides authentication, authorization, and accounting (AAA) services to a mobile ISP network for achieving legitimate mobility using e-mail-styled NAI and MAC valued keys in wireless IP access. In the rapidly expanding mobile environment, the introduction of identity-based cryptographic schemes has many advantages ranging from easy migration to public key cryptography. Accordingly, the current paper proposes a secure wireless Internet roaming service and WLAN service using identity(ID)-based cryptography. To support secure Mobile IP authentication between a mobile node and the authentication server, Mobile IP with an AAA protocol of mutual authentication is proposed using an ID-based signature scheme instead of a conventional MAC valued, symmetric, and single authentic protocol. Furthermore, the proposed protocol can also be implemented using algorithms based on elliptic curves.

Inspection of defect on LCD panel using polynomial approximation

Nowadays, the CRT display devices are rapidly substituted for LCD display devices. In LCD panel production, the inspection process relies on human vision. So, the results of inspection is likely to be subjective. Therefore, we need the automated inspection system for LCD devices by obtaining objective decision level. In this paper, we propose an efficient automated inspection algorithm using polynomial approximation and optimal thresholding technique. The experimental result shows us that our proposed system can have enough performance for substitution of human inspectors.

MR brain image segmentation using fuzzy clustering

In anatomical aspects, magnetic resonance (MR) imaging offers more accurate information for medical examination than other medical images such as X-ray, ultrasonic and CT images. In this paper, an automated segmentation and lesion detection algorithm are proposed for axial MR brain images. The proposed segmentation algorithm consists of two steps in order to reduce computation time for classifying tissues. In the first step, the cerebrum region is extracted by using thresholding, morphological operation, and labeling algorithm. In the second step, white matter, gray matter, and cerebrospinal fluid in the cerebrum are detected using fuzzy c-means (FCM) algorithm. The new lesion detection algorithm uses anatomical knowledge and local symmetry. A symmetric measure is defined to quantify the normality of MRI slice, which is based on the number of pixels, moment invariants, and Fourier descriptors. The proposed method has been applied to forty normal and abnormal slices. The experimental results show that the proposed segmentation algorithm is appropriate for classifying a large amount of axial brain MR data, and also show that the proposed lesion detection algorithm is successful.

Image normalization using invariant centroid for RST invariant digital image watermarking

Digital content services and tools have spread all over the world creating an acute need for robust copyright protection and ownership management systems. Robust watermarking technology is playing a crucial roll in these systems developments. This paper reports a robust technique for digital image watermarking. Salient image areas extracted from the pixel domain are used to embed local watermarks in the frequency domain. Relevant image corners are first extracted using well- established scale-space theories for edge and corner detection. Fairly small areas around each corner are used to insert the watermark. The objective is to achieve robustness against local and global geometric transformations as well as conventional image processing attacks while keeping the computational cost low. The DFT is applied on the discrete polar coordinates over asymmetric grids defined on uniform angles and non-uniform radii. The objective is to keep the rotation invariance property of the DFT magnitude while avoiding numerical and interpolation errors on the radii axis. A blind watermark detection process based on statistical correlation is used. Several experiments to validate the robustness of the proposed approach were conducted and are reported in the paper.

TFT-LCD panel Blob-Mura inspection using the correlation of wavelet coefficients

In this paper, we propose a Mura detection method in LCM panel using wavelet transform. Generally, the defect in LCM is so burred that the Mura boundary between defect and background is not clear. To detect and recognize exactly the boundary part of the defect, discrete wavelet transform is used. Then considering the relationship of wavelet coefficients, the significant and insignificant coefficients are separated. After the OR logical operation, closing morphological operation are performed to detect the Mura defect. By the experiment, the proposed method shows promising results for Mura detection in LCM panels.