• Journal of Electrical Engineering and Technology
• /
• v.9 no.5
• /
• pp.1762-1773
• /
• 2014

In this paper, a distributed image coding scheme for multi-view video through an efficient generation of side information is proposed. A distributed video coding technique corrects the errors in the side information, which is generated with the original image, by using the channel coding technique at the decoder. Therefore, the more correct the generated side information is, the better the performance of distributed video coding. The proposed technique is to apply the distributed video coding schemes to the image coding for multi-view video. It generates side information by selectively and efficiently using both 3-dimensional warping based on the depth map with spatially adjacent frames and motion-compensated temporal interpolation with temporally adjacent frames. In this scheme the difference between the adjacent frames, the sizes of the motion vectors for the adjacent blocks, and the edge information are used as the selection criteria. From the experiments, it was observed that the quality of the side information generated by the proposed technique was improved by the average peak signal-to-noise ratio of 0.97dB than the one by motion-compensated temporal interpolation or 3-dimensional warping. The result from analyzing the rate-distortion curves revealed that the proposed scheme could reduce the bit-rate by 8.01% on average at the same peak signal-to-noise ratio value, compared to previous work.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.35 no.3
• /
• pp.125-132
• /
• 2017

Even after applying an image registration, Very High Resolution (VHR) multi-temporal images acquired from different optical satellite sensors such as IKONOS, QuickBird, and Kompsat-2 show a local misalignment due to dissimilarities in sensor properties and acquisition conditions. As the local misalignment, also referred to as Registration Noise (RN), is likely to have a negative impact on multi-temporal information extraction, detecting and reducing the RN can improve the multi-temporal image processing performance. In this paper, an approach to fine registration between VHR multi-temporal images by considering local distribution of RN is proposed. Since the dominant RN mainly exists along boundaries of objects, we use edge information in high frequency regions to identify it. In order to validate the proposed approach, datasets are built from VHR multi-temporal images acquired by optical satellite sensors. Both qualitative and quantitative assessments confirm the effectiveness of the proposed RN-based fine registration approach compared to the manual registration.

• Journal of KIISE:Software and Applications
• /
• v.27 no.8
• /
• pp.804-814
• /
• 2000

In this paper, we propose an effective method to detect the regions of interests in the Videostrobokymography System. Videostrobokymography system is a medical image processing system for extracting automatically the diagnosis parameters from the irregular vibratory movements of the vocal fold. We detect the regions of interests through three steps. In the first step, we remove the noise in the input image and we find the minimum energy value in each frame. In the second step, we computed the edge by everage value for the one line. In the third step, the regions of interests can be extracted by using the Merge Algorithm which uses the variance of luminance as the feature points. We experimented this method for the vocal fold images of nineteen patients. In consequence, the regions of interests are detected in most vocal fold images. The method proposed in this study is efficient enough to extract the region of interests in the vocal fold images with the frame rate of 40 frames/second and the resolution of 200${\times}$280 pixels.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.6
• /
• pp.1162-1169
• /
• 2007

In this paper, we proposed a container identifier recognition method for containers used in harbors. After converting a real container image to a gray image, edges are detected from the gray image applying Prewitt mask and candidate identifier area is extracted using morphological features of individual identifier for identifying containers. Because noises are included in the extracted candidate identifier area, noises are eliminated and each identifier is separated using 4-directional edge tracking algorithm and Grassfire algorithm. Each identifier in the noise-free candidate identifier area is recognized using FCM-based row RBF network for discriminating containers. We used 300 real container images for experiment to evaluate the performance of the proposed method, and we could verify the proposed method is better than a conventional method.

• The Journal of the Korea Contents Association
• /
• v.19 no.1
• /
• pp.125-131
• /
• 2019

A vanishing point is a point on an image to which parallel lines projected from a real space gather. A vanishing point in a road space provides important spatial information. It is possible to improve the position of an extracted lane or generate a depth map image using a vanishing point in the road space. In this paper, we propose a method of detecting vanishing points on images taken from a vehicle's point of view using Deep Neural Network (DNN) and Histogram of Oriented Gradient (HoG). The proposed algorithm is divided into a HoG feature extraction step, in which the edge direction is extracted by dividing an image into blocks, a DNN learning step, and a test step. In the learning stage, learning is performed using 2,300 road images taken from a vehicle's point of views. In the test phase, the efficiency of the proposed algorithm using the Normalized Euclidean Distance (NormDist) method is measured.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.6
• /
• pp.525-534
• /
• 2018

Camera calibration is the process of determining the parameters such as the focal length of a camera, the position of a principal point, and lens distortions. For this purpose, images of checkerboard have been mainly used. When targets were automatically recognized in checkerboard image, the existing studies had limitations in that the user should have a good understanding of the input parameters for recognizing the target or that all checkerboard should appear in the image. In this study, a methodology for automatic target recognition was proposed. In this method, even if only a part of the checkerboard image was captured using rectangles including eight blobs, four each at the central portion and the outer portion of the checkerboard, the index of the target can be automatically assigned. In addition, there is no need for input parameters. In this study, three conditions were used to automatically extract the center point of the checkerboard target: the distortion of black and white pattern, the frequency of edge change, and the ratio of black and white pixels. Also, the direction and numbering of the checkerboard targets were made with blobs. Through experiments on two types of checkerboards, it was possible to automatically recognize checkerboard targets within a minute for 36 images.

• Journal of Aerospace System Engineering
• /
• v.13 no.4
• /
• pp.26-36
• /
• 2019

The precise alignment between optical components is required in high-resolution earth observation satellites. However, the misalignment of optical components occurs due to external factors such as severe satellite launch environment and space environment. A satellite optical system with a focus mechanism is required to compensate for the image quality degraded by these misalignments. This study designed, fabricated, aligned precisely, and carried out a performance tests for the image quality of the system. The satellite optical camera performance tests were carried out to check the image quality change by operating the focus mechanism and to analyze the satellite optical system MTF by photographing USAF target using the autocollimator. According to the experimental results, the misalignments can be compensated sufficiently with the focus mechanism. Finally the basic data for re-focusing algorithm of the optical system was obtained through this study.

• Journal of radiological science and technology
• /
• v.45 no.1
• /
• pp.11-17
• /
• 2022

This study was purpose to quantitative assessment of the resolution characteristics by using American college of radiology(ACR) phantom for magnetic resonance imaging (MRI). The MRI equipment was used (Achiva 3.0T MRI, Philips system, Netherlands) and the head/neck matrix shim SENSE head coil were 32 channels(elements) receive MR coil. And the MRI equipment was used (Discovery MR 750, 3.0T MRI, GE medical system, America) and the head/neck matrix shim MC 3003G-32R 32-CH head coil were receive MR coil. As for the modulation transfer function(MTF) comparison result by using ACR magnetic resonance imaging phantom, the MTF value of the ACR standard T2 image in GE equipment is 0.199 when the frequency is 1.0 mm^-1 and the MTF value of the hospital T2 image in Philips equipment is 0.528. It was used efficiently by using a general sequence more than the standard sequence method using the ACR phantom. In addition it is significant that the quantitative quality assurance evaluation method for resolution characteristics was applied mutatis mutandis, and the result values of the physical image characteristics of the 3.0T MRI device were presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.50-53
• /
• 2022

In order to detect an object in yolv5, a process of annotating location information on an existing image is required when learning an image. The most representative method is to draw a bounding box on an image to store location information as meta information. However, if the boundary of the object is ambiguous, it will be difficult to make a bounding box. A representative example would be to classify parts that are not fire and parts that are fire. Therefore, in this paper, images of 100 samples judged to have caught fire were learned by varying the number of boxes. The results showed better fire detection performance in the model where the bounding box was trained by annotating it with three boxes by segmenting it slightly more than annotating it with one box by holding the edge as large as possible during annotating it with one box.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.4
• /
• pp.47-57
• /
• 2009

Event detection and recognition is an active and challenging topic recent in Computer Vision. This paper describes a new method for recognizing events caused by human motion from video sequences in an office environment. The proposed approach analyzes human motions using Motion History Image (MHI) sequences, and is invariant to body shapes. types or colors of clothes and positions of target objects. The proposed method has two advantages; one is thant the proposed method is less sensitive to illumination changes comparing with the method using color information of objects of interest, and the other is scale invariance comparing with the method using a prior knowledge like appearances or shapes of objects of interest. Combined with edge detection, geometrical characteristics of the human shape in the MHI sequences are considered as the features. An advantage of the proposed method is that the event detection framework is easy to extend by inserting the descriptions of events. In addition, the proposed method is the core technology for event detection systems based on context-aware computing as well as surveillance systems based on computer vision techniques.