• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.631-634
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• 1999

In this work, a new algorithm for canceling MRI artifact in the image plane is presented. In the conventional approach, the motions in the X(readout) direction and Y(the phase encoding) direction are estimated simultaneously. However, the feature of each X and Y directional motion is different. First, we notice that the X directional motion corresponds to a shift of the X directional spectrum of the MRI signal, and the non zero area of the spectrum just corresponds to X axis projected area of the density function. So the motion is estimated by tracing the edges of the spectrum, and the X directional motion is canceled by shifting the spectrum in inverse direction. Next, the Y directional motion is canceled using a new constraint, with which the motion component and the true image component can be separated. This algorithm is shown to be effective by simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.2
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• pp.172-179
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• 1991

In this paper we have proposed an efficient coding algorithm using directional filtering. First an image is transformed by using DCT which has better energy compaction and then the transformed image is divided into a low frequency component and several high frequency components. The transformed coefficients of each parts are transmitted respectively by using huffman code and these are transformed inversely at receiver. For the directional components total edge images are reconstructed at zero crossing points. We are able to reduce the amount of data by getting of complex component and making directional angles 90. As a results, this proposed method is better than that of Kunt in respect of processing time and memories. We have 38dB of image quality with objective measurement of PSNR and 0.26bpp of compression ratio which is acceptable.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1639-1649
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• 2004

In this paper, a method for detection of forged signatures based on spectral analysis of directional gradient density function and a weighted fuzzy classifier is proposed. The well defined outline of an incoming signature image is extracted in a preprocessing stage which includes noise reduction, automatic thresholding, image restoration and erosion process. The directional gradient density function derived from extracted signature outline is highly related to the overall shape of signature image, and thus its frequency spectrum is used as a feature set. With this spectral feature set, having a property to be invariant in size, shift, and rotation, a weighted fuzzy classifier is evaluated for the verification of freehand and random forgeries. Experiments show that less than 5% averaged error rate can be achieved on a database of 500 signature samples.

• International Journal of Advanced Culture Technology
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• v.6 no.3
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• pp.173-177
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• 2018

Masks are generated by adding different fonts of learning data characters in pixel unit, and pixel values belonging to each of the masks are divided into 3 groups. Using the directional expansion operators, we expand the text area of the test data character into 4 diagonal directions in order to create the boundary areas to distinguish it from the background area. A mask with a minimum average discordance is selected as the final recognition result by calculating the degree of discordance between the expanded test data and the masks. Image comparison using directional expansion operations more accurately recognizes test data through 4 subdivided recognition processes. It is also possible to expand the ranges of 3 groups of pixel values of masks more evenly such that new fonts can easily be added to the given learning data.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.293-297
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• 2013

Delivery of high quality video over a wide area network with large number of users poses great challenges for the video communication system. To ensure video quality, multiple descriptions have recently attracted various attention as a way of encoding and visual information delivery over wireless network. We propose a new efficient multiple description coding (MDC) technique. Quincunx lattice sub-sampling is used for generating multiple descriptions of an image. In this paper, we propose the application of a directional discrete cosine transform (DCT) to a sub-sampled quincunx lattice to create an MDC representation. On the decoder side, the image is decoded from the received side information. If all the descriptions arrive successfully, the image is reconstructed by combining the descriptions. However, if only one side description is received, decoding is executed using an interpolation process. The experimental results show that such the directional DCT can achieve a better coding gain as well as energy packing efficiency than the conventional DCT with re-alignment.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.9
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• pp.887-893
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• 2012

In this paper, we propose a new approach to extract directional features based on directional patterns of each region in fingerprint images. The proposed approach computes the center of gravity to extract features from fingerprint images of various shapes. According to it, we divide a fingerprint image into four regions and compute the directional values of each region. To extract directional features of each region from a fingerprint image, we spilt direction values of ridges in a region into 18 classes and compute frequency distribution of each region. Through the result of our experiment using FVC2002 DB database acquired by electronic devices, we show that directional features are effectively extracted from various fingerprint images of exceptional inputs which lost all or part of singularities. To verify the performance of the proposed approach, we explained the process to model Arch, Left, Right and Whorl class using the extracted directional features of four regions and analyzed the classification result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2068-2086
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• 2011

Based on the quincunx sub-sampling grid, the New Interleaved Hierarchical INTerpolation (NIHINT) method is recognized as a superior pyramid data structure for the lossless and progressive coding of natural images. In this paper, we propose a new image interpolation algorithm, Edge Adaptive Hierarchical INTerpolation (EAHINT), for a further reduction in the entropy of interpolation errors. We compute the local variance of the causal context to model the strength of a local edge around a target pixel and then apply three statistical decision rules to classify the local edge into a strong edge, a weak edge, or a medium edge. According to these local edge types, we apply an interpolation method to the target pixel using a one-directional interpolator for a strong edge, a multi-directional adaptive weighting interpolator for a medium edge, or a non-directional static weighting linear interpolator for a weak edge. Experimental results show that the proposed algorithm achieves a better compression bit rate than the NIHINT method for lossless image coding. It is shown that the compression bit rate is much better for images that are rich in directional edges and textures. Our algorithm also shows better rate-distortion performance and visual quality for progressive image transmission.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.408-413
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• 2005

This paper presents a technique which extracts a moving object from omni-directional images and estimates a real coordinates of the moving object using 3D parabolic coordinate transformation. To process real-time, a moving object was extracted by proposed Hue histogram Matching Algorithms. We demonstrate our proposed technique could extract a moving object strongly without effects of light changing and estimate approximation values of real coordinates with theoretical and experimental arguments.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.686-692
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• 2006

This paper shows the calculation of 3D geometric information such as height, direction and distance under the constraints of a catadioptric camera system. The catadioptric camera system satisfies the single viewpoint constraints adopting hyperboloidal mirror. To calculate the 3D information with a single omni-directional image, the points are assumed to lie in perpendicular to the ground. The infinite plane is also detected as a circle from the structure of the mirror and camera. The analytic experiments verify the correctness of theory using real images taken in indoor environments like rooms or corridors. Thus, the experimental results show the applicability to calculate the 3D geometric information using single omni-directional images.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1075-1078
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• 1999

In this study, a new algorithm for canceling MRI artifacts through the translational motion of image plane is presented. Bloating is often makes problems in a clinical diagnosis. Assuming that the head moves up and down due to breathing, rigid translational motions in only y(phase encoding axis) direction is treated. First, we notice that the x directional motion corresponds to a shift of the x directional spectrum of the MRI signal, and the non zero area of the spectrum just corresponds to x axis projected area of the density function. So the motion is estimated by tracing the edges of the spectrum, and the x directional motion is canceled by shifting the spectrum in inverse direction. Next, the y directional motion is canceled using a new constraint, with which the motion component and the true image component can be separated. Finally, the effectiveness of this algorithm is shown by using a phantom with simulated motions.