• Journal of Broadcast Engineering
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• v.20 no.4
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• pp.521-532
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• 2015

This paper presents a piecewise image denoising with multi-scale block region detector based on quadtree structure for effective image restoration. Proposed piecewise image denoising method suggests multi-scale block region detector (MBRD) by dividing whole pixels of a noisy image into three parts, with regional characteristics: strong variation region, weak variation region, and flat region. These regions are classified according to total pixels variation between multi-scale blocks and are applied principal component analysis with local pixel grouping, bilateral filtering, and structure-preserving image decomposition operator called relative total variation. The performance of proposed method is evaluated by Experimental results. we can observe that region detection results generated by the detector seems to be well classified along the characteristics of regions. In addition, the piecewise image denoising provides the positive gain with regard to PSNR performance. In the visual evaluation, details and edges are preserved efficiently over the each region; therefore, the proposed method effectively reduces the noise and it proves that it improves the performance of denoising by the restoration process according to the region characteristics.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.1
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• pp.64-77
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• 2012

In this study, the crack detecting system with digital image processing techniques based on the mathematical morphology method was developed to detect cracks in concrete structures. In the developed system, the image combining technique of reconstructing multiple images as an entire single image considering efficient management of analysis results was applied as an additional module. The developed system was verified through a field test with the cracked concrete culvert and the crack width of 0.2 mm was able to be detected in the 40m span. In the image analysis, the difference between calculated crack width and actual crack width were less than 0.08mm. For image combination in the stitching test of pattern images, the stitched image was identical with the original picture of entire subject in the visual perception level.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.189-194
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• 2017

In this study, we propose a method which is based on "Image segmentation by histogram thresholding using hierarchical cluster analysis"/HCA/ and "A nonparametric approach for histogram segmentation"/NHS/. HCA method uses that all histogram bins are one cluster then it reduces cluster numbers by using distance metric. Because this method has too many clusters, it is more computation. In order to eliminate disadvantages of "HCA" method, we used "NHS" method. NHS method finds all local minima of histogram. To reduce cluster number, we use NHS method which is fast. In our approach, we combine those two methods to eliminate disadvantages of Arifin method. The proposed method is not only less computational than "HCA" method because combined method has few clusters but also it uses local minima of histogram which is computed by "NHS".

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1983.10a
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• pp.65-67
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• 1983

In this paper, two - dimensional digital filtering analysis of Korean chracter image and a method which groups and sorts these filtered patterns are Presented.

• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.643-654
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• 2003

This paper proposes slippage and rotation sensing method in tactile image of robot griper. To overcome the demerits of inaccurate taxel positional sensing generated by previous moment method and edge ＆ line method according to constraints of taxet number changing or minimum taxel number, the proposed method classified the sensing method into two classes such as pixel status analysis and decision factor determination. The decision factor determines taxel threshold for filtering and sensing method choice based on moment method and edge ＆ line method. Computer simulations and experiment result show that the proposed method enhances the slippage and rotation sensing than previous methods for tactile image.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.556-564
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• 2021

Numerous spatial and transform-domain-based conventional denoising algorithms struggle to keep critical and minute structural features of the image, especially at high noise levels. Although neural network approaches are effective, they are not always reliable since they demand a large quantity of training data, are computationally complicated, and take a long time to construct the model. A new framework of enhanced hybrid filtering is developed for denoising color images tainted by additive white Gaussian Noise with the goal of reducing algorithmic complexity and improving performance. In the first stage of the proposed approach, the noisy image is refined using a high-dimensional non-local means filter based on Principal Component Analysis, followed by the extraction of the method noise. The wavelet transform and SURE Shrink techniques are used to further culture this method noise. The final denoised image is created by combining the results of these two steps. Experiments were carried out on a set of standard color images corrupted by Gaussian noise with multiple standard deviations. Comparative analysis of empirical outcome indicates that the proposed method outperforms leading-edge denoising strategies in terms of consistency and performance while maintaining the visual quality. This algorithm ensures homogeneous noise reduction, which is almost independent of noise variations. The power of both the spatial and transform domains is harnessed in this multi realm consolidation technique. Rather than processing individual colors, it works directly on the multispectral image. Uses minimal resources and produces superior quality output in the optimal execution time.

• Journal of the Korean Society of Visualization
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• v.19 no.1
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• pp.28-35
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• 2021

In this study, an image processing method for the measurement of two-phase bubbly flow is developed. Shadowgraphy images obtained by high-speed camera are used for analysis. Some bubbles are generated as single unit and others are overlapped or clustered. Single bubbles can be easily analyzed using parameters such as bubble shape, centroid, and area. But overlapped bubbles are difficult to transform clustered bubbles into segmented bubbles. Several approaches were proposed for the bubble segmentation such as Hough transform, connection point method and watershed. These methods are not enough for bubble segmentation. In order to obtain the size distribution of bubbles, we present a method of splitting overlapping bubbles using watershed and approximating them to ellipse. There is only 5% error difference between manual and automatic analysis. Furthermore, the error can be reduced down to 1.2% when a correction factor is used. The ellipse fitting algorithm developed in this study can be used to measure bubble parameters accurately by reflecting the shape of the bubbles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2333-2345
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• 2024

Facial wrinkles are widely used to evaluate skin condition or aging for various fields such as skin diagnosis, plastic surgery consultations, and cosmetic recommendations. In order to effectively process facial wrinkles in facial image analysis, accurate wrinkle segmentation is required to identify wrinkled regions. Existing deep learning-based methods have difficulty segmenting fine wrinkles due to insufficient wrinkle data and the imbalance between wrinkle and non-wrinkle data. Therefore, in this paper, we propose a new facial wrinkle segmentation method based on a UNet++ model. Specifically, we construct a new facial wrinkle dataset by manually annotating fine wrinkles across the entire face. We then extract only the skin region from the facial image using a facial landmark point extractor. Lastly, we train the UNet++ model using both dice loss and focal loss to alleviate the class imbalance problem. To validate the effectiveness of the proposed method, we conduct comprehensive experiments using our facial wrinkle dataset. The experimental results showed that the proposed method was superior to the latest wrinkle segmentation method by 9.77%p and 10.04%p in IoU and F1 score, respectively.

• Computers and Concrete
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• v.7 no.3
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• pp.239-247
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• 2010

A proposed topology method is introduced to measure the air content of fresh cement paste and hardened concrete. The method takes advantage of chromatographic analysis in void areas that are highlighted using different color schemes and later calculated using built-in computer software. The air content measured by the topology method is compared with results obtained from the conventional ASTM methods. It is concluded that the proposed method is reliable, and costs less and is easier to operate compared with the ASTM methods. In addition, 3 dimensional pore models can be created using image post-processing techniques. The proposed method helps researchers in understanding the formation and existence of concrete pores. This paper reports a detailed test program demonstrating the standard operating procedure used for the proposed method and presents a comparison of results between the proposed method and conventional ASTM Specifications. It is also concluded that the air content increases with increasing size of pores and increasing percentage of coarse aggregates.

• Korean Journal of Agricultural Science
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• v.49 no.3
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• pp.667-678
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• 2022

A characteristic of a region's environmental resources is the competitiveness of local agricultural products. This study explores methods of making locally produced agricultural products appealing to consumers. We looked at ways to appeal to consumers by using the image of environment resource and environment-agriculture product image congruence. The relationships of two dimensions of environmental image, perceived quality and purchase intention, are examined. From the results of the study, both the image of environment resource and environment-agriculture product image congruence have a positive effect on purchasing local agricultural products through perceived quality. This study tried to ascertain which of the two dimensions of the environmental image factor is more effective in terms of consumer appeal for local agricultural products. As a result, both the image of environment resource and environment-agricultural product image congruence are found to have a positive effect on the purchase intention of consumers through perceived quality. By comparing the paths of the two dimensions it is found that the method of appealing to consumers by using the environment-agriculture product image congruence is more effective. The results of this study present an effective method of making locally produced agricultural products appealing to consumers and suggest an effective strategic direction for selling local agricultural products.