• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.137-138
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• 2018

이미지의 픽셀 기반 처리는 한 픽셀의 값을 변환하고 다른 픽셀의 값에 관계없이 현재 픽셀의 값에 따라 변환하는 프로세스를 의미한다. 픽셀 기반 처리는 이미지 변환, 이미지 향상 및 이미지 합성과 같은 많은 분야에서 가장 기본적인 작업이다. 본 논문에서는 히스토그램 연산과 같은 영상의 전처리 과정이 경계 검출 결과에 미치는 상호 연관성에 대해 알아보고 픽셀 기반의 처리를 이용하여 효과적으로 영상의 윤곽을 찾는 방법을 제안한다.

• KIISE Transactions on Computing Practices
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• v.21 no.6
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• pp.424-429
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• 2015

This research proposes a new system for calculating the total amount of coins in an image. The proposed system identified and classified the coins in the image in realtime. The image was obtained using a USB camera. Most previous coin calculation systems only used size information. If the size of an object was incorrectly detected, it caused a misclassification. Especially, in case of the former 10 won, it had high error rate because it was similar in size to the 50 won and 100 won coin. The proposed system combines hue histogram information with size information to reduce errors in the classification process. When we only used size information in the classification experiment of 2,290 coins, the recognition rate was on average about 88.2%. When we combined hue information with size information the recognition rate increased to about 99.3%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.5
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• pp.540-546
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• 2019

This study suggests a binarization method that minimizes information loss for night illumination images. The object of the night illumination image is an image which is not focused due to the influence of illumination and is not identifiable. Also, the image has a brightness area in only a part of the brightness histogram. So the existing simple binarization method is hard to get good results. The proposed binarization method uses image segmentation method and image merging method. In the stepwise divided blocks, we divide into two regions using the triangular type of fuzzy logic. The value 0 of the membership degree is binarized at the present step, and the value of the membership degree 1 is binarized after the next step. Experimental results show that night illumination images with minimal loss of information can be obtained in a dark area brightness range.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.349-356
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• 2004

The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. In this paper we propose and evaluate a novel recognition algorithm for container identifiers that effectively overcomes these difficulties and recognizes identifiers from container images captured in various environments. The proposed algorithm, first, extracts the area containing only the identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper. Then a contour tracking method is applied to the binarized area in order to extract the container identifiers which are the target for recognition. In this paper we also propose and apply a novel ART2-based hybrid network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm performs better for extraction and recognition of container identifiers compared to conventional algorithms.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.88-95
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• 2003

The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. We proposed and evaluated the novel recognition algorithm of container identifiers that overcomes effectively the hardness and recognizes identifiers from container images captured in the various environments. The proposed algorithm, first, extracts the area including only all identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper and by applying contour tracking method to the binarized area, container identifiers which are targets of recognition are extracted. We proposed and applied the ART2-based RBF network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm has more improved performance in the extraction and recognition of container identifiers than the previous algorithms.

• Journal of ILASS-Korea
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• v.29 no.2
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• pp.91-97
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• 2024

When investigating the droplet, spray, and impact of liquid on a solid plate, backlight imaging has been widely used to understand these phenomena. However, some previous studies have suffered from poor image quality. In this study, various combinations of image processing algorithms, such as white image correction, histogram equalization, CLAHE, Otsu's binarization, and multi-Otsu's binarization, have been applied to flash boiling spray images to enhance image quality for qualitative observation and semi-quantitative spray angle evaluation. To acquire images with high contrast for qualitative observation, applying CLAHE was effective, making small droplets and detailed shapes of the jet noticeable. However, when images were averaged to determine spray angle or penetration length based on intensity, this method induced artifact unphysical patterns, thus requiring careful consideration. Based on the algorithm proposed in this study, the spray angle variation according to injection pressure and temperature has been calculated, showing a reasonable trend.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.217-227
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• 2017

Crosswalk detection is an important part of the Pedestrian Protection System in autonomous vehicles. Different methods of crosswalk detection have been introduced so far using crosswalk edge features, the distance between crosswalk blocks, laser scanning, Hough Transformation, and Fourier Transformation. However, most of these methods failed to detect crosswalks accurately, when they are damaged, faded away or partly occluded. Furthermore, these methods face difficulties when applying on real road environment where there are lot of vehicles. In this paper, we solve this problem by first using a region based binarization technique and x-axis histogram to detect the candidate crosswalk areas. Then, we apply Support Vector Machine (SVM) based classification method to decide whether the candidate areas contain a crosswalk or not. Experiment results prove that our method can detect crosswalks in different environment conditions with higher recognition rate even they are faded away or partly occluded.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.466-471
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• 2007

Conventional thresholding methods including Otsu's thresholding method are based on the gray levels frequency histogram. But the gray levels frequency histogram is obtained by recomposing only frequency information from an input image, where frequency histogram dose not contain any other informations such as the distribution of gray levels and relation between gray levels. Therefore the methods using the gray levels frequency histogram occasionally present inappropriate threshold values because it cannot reflect informations of the given image sufficiently. In this paper, we define a correlation function of gray levels and propose a novel thresholding method using the gray levels frequency histogram and the spatial correlation information. The effectiveness of the proposed method will be shown through comparison with Otsu's thresholding method.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.265-270
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• 2011

In this paper, we propose a method for intensity correction using binarization-based region segmentation in 3D stereoscopic images. In the proposed method, 3D stereoscopic right image is segmented using binarizarion. Small regions in the segmented image are eliminated. For each region in right image, a corresponding region in left image is decided through region matching using correlation coefficient. When region-based matching, in order to prevent overlap between regions, we remove a portion of the area closed to the region boundary using morphological filter. The intensity correction in left and right image can be performed through histogram specification between the corresponding regions. Simulation results show the proposed method has the smallest matching error than the conventional method when we generate the right image from the left image using block based motion compensation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.5
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• pp.24-32
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• 2010

In this study, we have proposed a pre-processing algorithm newly developed for improving the tracking efficiency of the optical flow method. The developed pre-processing algorithm consists of a median filter, binarization, morphology, canny edge, contour detecting and an approximation method. In order to evaluate whether the optical flow tracking capacity increases, this study applied the pre-processing algorithm to the Lucas-Kanade(LK) optical flow algorithm, and comparatively analyzed its images and tracking results with those of optical flow without the pre-processing algorithm and with the existing pre-processing algorithm(composed of median filter and histogram equalization). As a result, it was observed that the tracking performance derived from the LK optical flow algorithm with the pre-processing algorithm, shows better tracking accuracy, compared to the one without the pre-processing algorithm and the one with the existing pre-processing algorithm. It seems to have resulted by successful segmentation for characteristic areas and subdivision into inner and outer contour lines.