• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.583-599
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• 2022

Although the object detection accuracy with a single image has been significantly improved with the advance of deep learning techniques, the detection accuracy for pig monitoring is challenged by occlusion problems due to a complex structure of a pig room such as food facility. These detection difficulties with a single image can be mitigated by using a video data. In this research, we propose a method in pig detection for video monitoring environment with a static camera. That is, by using both image processing and deep learning techniques, we can recognize a complex structure of a pig room and this information of the pig room can be utilized for improving the detection accuracy of pigs in the monitored pig room. Furthermore, we reduce the execution time overhead by applying a pruning technique for real-time video monitoring on an embedded board. Based on the experiment results with a video data set obtained from a commercial pig farm, we confirmed that the pigs could be detected more accurately in real-time, even on an embedded board.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.532-535
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• 2005

These days, many image processing techniques have been studied for effective image compression. Among those, 2D image filtering is widely used for 2D image processing. The 2D image filtering can be implemented by performing ID linear filtering separately in the direction of horizontal and vertical. Efficiency of image compression depends on what filtering method is used. Generally, circular convolution is widely used in the 2D image filtering for image processing. However it doesn't consider correlations at the region of image boundary, therefore filtering can not be performed effectively. To solve this problem. I proposed new convolution technique using Symmetric-Mirroring convolution, satisfying the 'alias-free' and 'error-free' requirement in the reconstructed image. This method could provide more effective performance than former compression methods. Because it used very high correlative data when performed at the boundary region. In this paper, pre-processing filtering in H.264 codec was adopted to analyze efficiency of proposed filtering technique, and the simulator developed by Matlab language was used to examine the performance of the proposed method.

• Imaging Science in Dentistry
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• v.44 no.1
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• pp.31-35
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• 2014

Purpose: This study was performed to investigate the effect of image enhancement of periapical radiographs according to the diagnostic task. Materials and Methods: Eighty digital intraoral radiographs were obtained from patients and classified into four groups according to the diagnostic tasks of dental caries, periodontal diseases, periapical lesions, and endodontic files. All images were enhanced differently by using five processing techniques. Three radiologists blindly compared the subjective image quality of the original images and the processed images using a 5-point scale. Results: There were significant differences between the image quality of the processed images and that of the original images (P< 0.01) in all the diagnostic task groups. Processing techniques showed significantly different efficacy according to the diagnostic task (P< 0.01). Conclusion: Image enhancement affects the image quality differently depending on the diagnostic task. And the use of optimal parameters is important for each diagnostic task.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.648-661
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• 1997

This paper presents a new method for post-processing of coded images based upon the low-pass filtering followed by the projection onto the NQCS (narrow quantization constraint set). We also investigate how the proposed method works on JPEG-coded real images. The starting point of the QCS-based post-processing techniques is the centroid of the QCS, where the original image belongs. The low-pass filtering followed by the projection onto the QCS makes the images lie on the boundary of the QCS. It is likely that, however, the original image is inside the QCS. Hence projection onto the NQCS gives a lower MSE (mean square error) than does the projection onto the QCS. Simulation results show that setting the narrowing coefficients of the NQCS to be 0.2 yields the best performance in most cases. Even though the JPEG-coded image is low-pass filtered and projected onto the NQCS repeatedly, there is no guarantee that the resultant image has a lower MSE and goes closer to the original image. Thus only one iteration is sufficient for the post-processing of the coded images. This is interesting because the main drawback of the iterative post-processing techniques is the heavy computational burden. The single iteration method reduces the computational burden and gives us an easy way to implement the real time VLSI post-processor.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.6
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• pp.626-634
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• 2011

The investigation of concrete structure typically relies on visual inspection which is one of the basic inspection techniques. Image processing techniques play a crucial role in the growing field of automatic surface inspection technique. However, kinds of inspection equipment, environmental condition and detection algorithm have much influence on the reliability of inspection result. This paper proposes a verification method and testing procedure for the reliability of inspection results and surveys characteristics of image acquisition systems and crack inspection algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.311-314
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• 1995

This paper presents a method for measuring tool wear parameters based on two dimensional image information. The tool wear images were obtained from an ITV camera with magnifying and lighting devices, and were analyzed using image processing techniques such as thresholding, noise filtering and boundary tracing. Thresholding was used to transform the captured gray scale image into a binary image for rapid sequential image processing. The threshold level was determined using a novel technique in which the brightness histograms of two concentric windows containing the tool wear image were compared. The use of noise filtering and boundary tracing to reduce the measuring errors was explored. Performance tests of the measurement precision and processing speed revealed that the direct method was highly effective in intermittent tool wear monitoring.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.1
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• pp.17-27
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• 2021

In this paper, we develop a galaxy image classification method based on hand-crafted features and machine learning techniques. Additionally, we provide an empirical analysis to reveal which combination of the techniques is effective for galaxy image classification. To achieve this, we developed a framework which consists of four modules such as preprocessing, feature extraction, feature post-processing, and classification. Finally, we found that the best technique for galaxy image classification is a method to use a median filter, ORB vector features and a voting classifier based on RBF SVM, random forest and logistic regression. The final method is efficient so we believe that it is applicable to embedded environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.67-69
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• 2021

Weather radar images can be used in a variety of ways because of their high visibility in terms of visuals. In other words it has the advantage of being able to grasp the flow of weather phenomena using not only the raw data of the weather radar, but also the change characteristics between consecutive images. In particular image processing techniques are gradually expanding in the field of meteorological research, and in the case of image data having high resolution such as weather radar images it is expected to produce useful information through a new approach called image processing techniques. In this study the weather phenomena flow was calculated as a vector from the change of the weather radar image according to time interval with the optical flow method, one of the image processing techniques. The characteristics of the weather phenomena to be analyzed were derived through vector analysis resolution suitable for the scale of weather, vector interpolation in regions where no radar echo exists, and the removal of relative flow vectors to distinguish the flow of specific weather and the entire atmosphere. Through this study, it is expected that not only the use of raw data of weather radar, but also the widening of the application area of weather radar, such as the use of unique characteristics of image data, and the active use of image processing techniques in the field of meteorology in the future.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1232-1235
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• 2002

An experiment on the automatic population measurement of brown Mealy Bugs is first reported in this article. Several image processing techniques are employed along with mapping function and neural network. Though brown Mealy Bugs are difficult to detect because of their camouflage, the experimental results showed that approximately 74% of them were correctly detected.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.11 no.2
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• pp.52-57
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• 2012

In this paper describe configuration about QCM system for image processing device. It presents that QCM's image processing board video from the camera recognized by the PLC's battery removable exact location coordinates to the robot image processing technology to deliver. In addition, QCM video image processing technology for improved data reliability is described. In this paper define the landmarks of battery for obtaining the location coordinates and verify battery the location coordinates acquisition process from field tests of the QCM/QTPE-BUS Battery Exchange System.