• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.1-10
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• 2002

This paper presents the new template based human face recognition methods to improve the recognition performance against scale and in-plane rotation variations of face images. To enhance the recognition performance, the templates are generated by linear or nonlinear operation on multiple images including different scales and rotations of faces. As the invariant features to allow for scale and rotation variations of face images, we adopt the affine transformation, the log-polar mapping, and the log-polar image based FFT. The proposed recognition methods are evaluated in terms of the recognition rate and the processing time. Experimental results show that the proposed template based methods lead to higher recognition rate than the single image based one. The affine transformation based face recognition method shows marginally higher recognition rate than those of the log-polar mapping based method and the log-polar image based FFT, while, in the aspect of processing time, the log-polar mapping based method is the fastest one.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.8
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• pp.88-100
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• 1999

Detecting human face and facial landmarks automatically in an image is as essential step to a fully automatic face recognition system. In this paper, we present a new approach to detect automatically face and its eyes of input image with scale and rotation variations of faces by using an intensity based template matching with a single log-polar face template. In a template-based matching it is necessary to normalize the scale changes and rotations of an input image to a template ones. The log-polar mapping which simulates space-variant human visual system converts scale changes and rotations of input image into constant horizontal and cyclic vertical shifts in the output plane. Intelligent use of this property allows us to shift of the candidate log-polar faces mapped at various fixation points of an input image to be matched to a template over the log-polar plane. Thus, the proposed method eliminates the need of adapting multitemplate and multiresolution schemes, which inevitably give rise to intensive computation involved to cope with scale and rotation variations of faces. Through this scale and rotation involved to cope with scale and method can lead to detecting face and its eyes simultaneously. Experimental results on a database of 795 images show over 98% detection rate.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.675-678
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• 2000

This paper presents a parametric line equation on the log-polar mapped plane to detect the straight lines in an original image. The log-polar edge image used in Hough transform is constructed by combining the edge images of both fovea and periphery. The foveal edge image detected by a Sobel mask on the Cartesian plane is transformed to the log-polar plane by forward mapping but the edge detection of the peripheral region is obtained by directly applying the newly developed mask to the log-polar plane. This paper also proposes a analytic method then determining a border between the fovea and the periphery regions.

• International Journal of Precision Engineering and Manufacturing
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• v.9 no.4
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• pp.45-50
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• 2008

The Fourier-Mellin transform is the theoretical basis for the translation, rotation, and scale invariance of an image. However, its implementation requires a log-polar map of the original image, which requires logarithmic sampling of a radial variable in that image. This means that the mapping process is accompanied by considerable loss of data. To solve this problem, we propose a dual log-polar map that uses both a forward image map and a reverse image map simultaneously. Data loss due to the forward map sub-sampling can be offset by the reverse map. This is the first step in creating an invertible log-polar map. Experimental results have demonstrated the effectiveness of the proposed scheme.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.4
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• pp.455-461
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• 2002

This paper presents a new parametric log line equation of polar form for Hough transform in log-polar plane, in which it can remove the well-known unboundedness problem of Hough parameters. Bolduc's method is used to generate a log-polar image dividing the fovea and periphery from a Cartesian image. Edges of the fovea and periphery are detected by using the Sobel mask and the proposed space-variant gradient mask, and are combined in the log-polar plane. The sampled points that might constitute a log line are quite sparse in a deep peripheral region due to severe under-sampling, which is an inherent property of LPM. To cope with such under-sampling, we determine the values of cumulative cells in Hough space by using the space-variant weighting. In our experiments, the proposed method demonstrates its validity of detecting not only the lines passing through both the fovea and periphery but also the lines in a deep periphery.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.15-18
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• 2000

In this study, we improve the performance of a speech recognition system of visual information depending on lip movements. This paper focuses on the robustness of the word recognition system with the rotation, transition and scaling of the lip images. The different methods of lipreading have been used to estimate the stability of recognition performance. Especially, we work out the special system of the log-polar mapping, which is called Mellin transform with quasi RTS-invariant and related approaches to machine vision. The results of word recognition are reported with HMM (Hidden Markov Model) recognition system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.379-385
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• 2004

Medical images are being managed more by PACS in general medical institutions. It is important to protect patients from being invaded their privacy related to the images. It is also necessary to confirm the ownership, the right of property of the medical images and notice whether the data are modified. In this paper, we propose a robust watermarking against RST attacks in medical images on the PACS. The proposed scheme modifies and improves Log-Polar Mapping and Fourier Mellin Transform in order to realize and recover serious image degradation and watermark data loss caused by the conversion between cartesian coordinate and log-polar coordinate. We used the radius and theta Look Up Table to solve the realization of the Fourier Mellin Transform, and inserted a watermark into 2D-DFT magnitudes using Spread Spectrum. Experimental results shows that this method are robust to rotation attack.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.34.1-34
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• 2002

1. Introduction 2. Focus of Expansion 3. Log-Polar Mapping 4. Egomotion and Optical Flow 5. Experimental Results 6. Conclusion. References.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.255-258
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• 2003

Recently, Digital Watermarking is used to authenticate data and to determine whether the data are distorted or not in medical images which is digitalized. The Fourier Mellin method using the Fourier Transform and the Log-Polar coordinate transform gets an invariant feature for RST distortion in images. But there are several problems in the real materialization. Interpolation of the image value should be considered according to the pixel position and so a watermark loss, original image distortion, numerical approximation is happened. Therefore there should be solved to realization of the Fourier Mellin method. Using the Look up table, there reduce the data loss caused by the conversion between Rectangular and Polar coordinate. After diagnose, medical images are transformed the Polar coordinate and taken the Discrete Fourier transform in the center of ROI region. Maintaining the symmetry in Fourier magnitude coefficient, the gaussian distributed random vectors and binary images are embedded in medical images.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.15-22
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• 2005

In this paper, we propose a face recognition system by using the CCD color image. We first get the face candidate image by using YCbCr color model and adaptive skin color information. And we use it initial curve of active contour model to extract face region. We use the Eye map and mouth map using color information for extracting facial feature from the face image. To obtain center point of Log-polar image, we use extracted facial feature from the face image. In order to obtain feature vectors, we use extracted coefficients from DCT and wavelet transform. To show the validity of the proposed method, we performed a face recognition using neural network with BP learning algorithm. Experimental results show that the proposed method is robuster with higher recogntion rate than the conventional method for the rotation and scale variant.