• Journal of the Optical Society of Korea
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• v.15 no.4
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• pp.335-339
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• 2011

Recently, we reported a single input channel joint transform correlator for the color pattern recognition which decomposes the input color image into three R, G, and B gray components and adds those components into a single gray image in the input plane. This technique has the merit of a single input channel instead of three input channels. However, we found this technique has some problems with discrimination impossibility in the case of a simple primary color pattern which results in the same gray level through the addition process. Thus, we propose a modified coding technique which selectively recombines the decomposed three R, G, and B gray components instead of the simple adding process. Simulated results show that the modified coding technique can accurately discriminate a variety of kinds of color images.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.248-251
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• 2014

We develop the signal processing method for implementing the human perceptual variant on frequency and space. The human visual perceptual sensitivity varies as frequency components and the human perceivable resolution diminishes as the distances further from the eye-focused point. For realizing the frequency sensitivity, we developed the signal direction adaptive multiband energy scaling method to weight the frequency components. The low-pass filtering is designed on the developed energy scaling method for diminishing perceivable resolutions as the deviated distance from the eye-focused point. The developed method not only enhances the frequency components of image signals at the eye-focused region but also smoothes non-perceivable detailed image signals at non-focused regions. The proposed method is verified by the subjective and objective evaluations that it can improve human perceptual visual quality.

• Smart Media Journal
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• v.4 no.3
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• pp.44-49
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• 2015

Text line segmentation is a preprocessing step in OCR, which can significantly influence the accuracy of document analysis applications. This paper proposes a novel methodology for the text line segmentation of handwritten documents. First, the average width of the connected components is used to form a 1-D Gaussian kernel and a smoothing operation is then applied to the input binary image. The adaptive binarization of the smoothed image forms the final text lines. In this work, the segmentation method involves two stages: firstly, the large connected components are labelled as a unique text line using text line area mapping. Secondly, the final refinement of the segmentation is performed using the Euclidean distance between the text line and small connected components. The group of uniquely labelled text candidates achieves promising segmentation results. The proposed approach works well on Korean and English language handwritten documents captured using a camera.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.260-264
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• 1987

Algorithms to detect in real-time both position and orientation of rectangular type electronic components are developed for industrial vision. In order to conduct detection in real-time, parallel processing algorithm of image date which uses several control processor is proposed. Image processing area is divided into several regions which can be processed by each cpu. As a result, processing time is improved when two control processors are used and real-time pattern recognition of not-well-aligned components is accomplished.

• International Journal of Contents
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• v.9 no.3
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• pp.1-9
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• 2013

In this paper, we propose a fast and accurate system for detecting pedestrians from a static image. Histogram of Oriented Gradients (HOG) is a well-known feature for pedestrian detection systems but extracting HOG is expensive due to its high dimensional vector. It will cause long processing time and large memory consumption in case of making a pedestrian detection system on high resolution image or video. In order to deal with this problem, we use Principal Components Analysis (PCA) technique to reduce the dimensionality of HOG. The output of PCA will be input for a linear SVM classifier for learning and testing. The experiment results showed that our proposed method reduces processing time but still maintains the similar detection rate. We got twenty five times faster than original HOG feature.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.275-288
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• 2023

Many image edge details are easily lost in the image denoising process, and the smooth image regions are prone to produce jagged. In this paper, we propose a wavelet-based image global k- singular value decomposition variational method to remove image noise. A layer of wavelet decomposition is applied to the noisy image first. Then, the image global k-singular value decomposition (IGK-SVD) method is used to remove the random noise of low-frequency components. Furthermore, a constructed variational denoising method (VDM) removes the random noise in the high-frequency component. Finally, the denoised image is obtained by wavelet reconstruction. The experimental results show that the proposed method's peak signal-to-noise ratio (PSNR) value is higher than other methods, and its structural similarity (SSIM) value is closer to one, indicating that the proposed method can effectively suppress image noise while retaining more image edge details. The denoised image has better denoising effects.

• Journal of Distribution Science
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• v.12 no.1
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• pp.21-28
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• 2014

Purpose - This study aims to examine the Indian consumers'mall shopping patronage with the application of theory of planned behavior (TPB). The research intends to extend the TPB components (attitude, self-efficacy, subjective norms) with the addition of self-image and study their effect on Indian consumers' mall patronage intention. Research design, data and methodology - The research employed factor analysis to verify correct loading of items on corresponding factors and to confirm the applicability of constructs in the Indian context. The model was tested using stepwise regression analysis. Results -The results indicate a positive relationship between self-efficacy and intention to mall patronage. The findings show that self-image, attitude, self-efficacy, subjective norm significantly influence the mall patronage intention. Self-efficacy, which signifies self-competence and confidence in one's ability as a mall shopper indicates that as the self-efficacy increases Indian consumers' will eventually patronize malls. Conclusions - Self-image congruency plays a salient role in predicting mall-shopping patronage. The mall management should ensure that the mall marketing strategies incorporate it along with the other components of TPB to warrant decent footfall.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.161-166
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• 2011

We present a fast algorithm for Korean text extraction and segmentation from subway signboards using smart phone sensors in order to minimize computational time and memory usage. The algorithm can be used as preprocessing steps for optical character recognition (OCR): binarization, text location, and segmentation. An image of a signboard captured by smart phone camera while holding smart phone by an arbitrary angle is rotated by the detected angle, as if the image was taken by holding a smart phone horizontally. Binarization is only performed once on the subset of connected components instead of the whole image area, resulting in a large reduction in computational time. Text location is guided by user's marker-line placed over the region of interest in binarized image via smart phone touch screen. Then, text segmentation utilizes the data of connected components received in the binarization step, and cuts the string into individual images for designated characters. The resulting data could be used as OCR input, hence solving the most difficult part of OCR on text area included in natural scene images. The experimental results showed that the binarization algorithm of our method is 3.5 and 3.7 times faster than Niblack and Sauvola adaptive-thresholding algorithms, respectively. In addition, our method achieved better quality than other methods.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11
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• pp.3592-3602
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• 2000

Image processing consist of image analysis and classification. The one is extracting of feature value in the image. The other is segimentationof image that have same properiv. A novel approach for the analysis and classification of tezture images based on statistical texture prunitive estraction are proposed. In this approach, feature vector extracting is based on stalisucal method using apatial dependence of grey level and use general lexture proerty. In is advantageous that not effiected on structure and type of lexture. These components describe the amount of roughness and softness of texture images Two leatures. Moment and Homogeneity, are componted from GLCM(gray level co-occurrence matrices) of the lexture promitive to charactenize statisical properties of the image. We show the successful experimental results by considerationof these two components fro the analysis and classificationto regular and irregular texture images.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.413-413
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• 2000

In this paper, we propose a series of calibrations f3r the x-ray three dimensional imaging system. In the developed x-ray system, a three dimensional inner and outer shape of an object can be reconstructed out of two dimensional transmitted x-ray image set, which are acquired by projecting x-ray to the object from different views. To achieve this, a reconstruction algorithm which estimates and updates the three dimensional volume from x-ray images is developed. The algorithm is named as uniform and simultaneous algebraic reconstruction technique(USART) which is an iterative method estimating a 3D volume based on its projected images. In this method, it is assumed that the imaging conditions that are the relative positions between the x-ray sources, object and the image planes are blown. Practically it is not easy to know the three dimensional coordinate of the components of the system, since the x-ray is not visible and the image distortions are present due to the optical components in the system. In this paper, methods of correcting image distortions are present firstly. Then the coordinates of the x-ray systems are calibrated from the x-ray images of the grid pattern. Some experimental results on these calibrations are present and discussed.