• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1553-1559
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• 2017

This paper proposes a lane departure detection algorithm using a single camera equipped in front of a vehicle. The proposed algorithm generates a partial top-view image for a small ROI (region of interest) designated on the top-view space form the image acquired by the camera, detects lanes on the small partial top-view image, and makes a decision on the lane departure by checking overlap between the pre-assigned virtual vehicle and the detected lanes. The proposed algorithm also includes the removal of lines occurred by road symbols (noises) disturbing the lane departure detection between lanes and the prediction of lost lanes using lane information of previous fames. In lane departure detection test using real road videos, the proposed algorithm makes the right decision of 99.0% in lane keeping conditions and 94.7% in lane departure conditions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.543-548
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• 2021

The higher the resolution of the image, the higher the satisfaction of the viewers of the image, and the super-resolution imaging has a considerable increase in research value among the fields of computer vision and image processing. In this study, the main features of low-resolution image LR are extracted mainly using deep learning super-resolution models. It learns and reconstructs the extracted features, and focuses on reconstruction-based algorithms that generate high-resolution image HR. In this paper, we investigate SRCNN and VDSR in a super-resolution algorithm model based on reconstruction. The structure and algorithm process of the SRCNN and VDSR model are briefly introduced, and the multi-channel and special form are also examined in the improved performance evaluation function, and understand the performance of each algorithm through experiments. In the experiment, an experiment was performed to compare the results of the SRCNN and VDSR models with the peak signal-to-noise ratio and image structure similarity, so that the results can be easily judged.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.464-470
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• 2016

This paper presents a speech recognition database verification system using speech measures, and describes a speech measure extraction algorithm which is applied to this system. In our previous study, to produce an effective speech quality measure for the system, we propose a combination of various speech measures which are highly correlated with WER (Word Error Rate). The new combination of various types of speech quality measures in this study is more effective to predict the speech recognition performance compared to each speech measure alone. In this paper, we increase the system independency by employing GMM acoustic score instead of HMM score which is obtained by a secondary speech recognition system. The combination with GMM score shows a slightly lower correlation with WER compared to the combination with HMM score, however it presents a higher relative improvement in correlation with WER, which is calculated compared to the correlation of each speech measure alone.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.146-155
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• 1997

The new video coding standard Iv1PEG-4 is enabling content-based functionalities. It requires a prior decomposition of sequences into video object planes (VOP's) so that each VOP represents moving objets. This paper addresses an image segmentation method for separating moving objects from still background (non-moving area) in video sequences using a statistical hypothesis test. In the proposed method. three consecutive image frames are exploited and a hypothesis testing is performed by comparing two means from two consecutive difference images. which results in a T-test. This hypothesis test yields a change detection mask that indicates moving areas (foreground) and non-moving areas (background), Moreover. an effective method for extracting

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.3
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• pp.1-10
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• 2020

In this paper, we propose an algorithm for estimating blood pressure using ECG (Electrocardiogram) and PPG (Photoplethysmography) signals. To estimate the BP (Blood pressure), we generate a periodic input signal, remove the noise according to the differential and threshold methods, and then estimate the systolic and diastolic blood pressures based on the convolutional neural network. We used 49 patient data of 3.1GB in the MIMIC database. As a result, it was found that the prediction error (RMSE) of systolic BP was 5.80mmHg, and the prediction error of diastolic BP was 2.78mmHg. This result confirms that the performance of class A is satisfied with the existing BP monitor evaluation method proposed by the British High Blood Pressure Association.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.93-98
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• 2012

Recently, we can easily create high resolution images with digital cameras for high-performance and make use them at variety fields. Especially, the image stitching method which adjusts couple of images has been researched. Image stitching can be used for military purposes such as satellites and reconnaissance aircraft, and computer vision such as medical image and the map. In this paper, we have proposed fast image stitching based on improved SURF algorithm using meaningful features in the process of images matching after extracting features from scenery image. The features are extracted in each image to find out corresponding points. At this time, the meaningful features can be searched by removing the error, such as noise, in extracted features. And these features are used for corresponding points on image matching. The total processing time of image stitching is improved due to the reduced time in searching out corresponding points. In our results, the processing time of feature matching and image stitching is faster than previous algorithms, and also that method can make natural-looking stitched image.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.43-57
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• 2009

Integrating 3D data acquired in multiple views is one of the most important techniques in 3D modeling. However, the existing integration methods are sensitive to registration errors and surface scanning noise. In this paper, we propose a integration algorithm using the local surface topology. We first find all boundary vertex pairs satisfying a prescribed geometric condition in the areas between neighboring surfaces, and then separates areas to several regions by using boundary vertex pairs. We next compute best fitting planes suitable to each regions through PCA(Principal Component Analysis). They are used to produce triangles that be inserted into empty areas between neighboring surfaces. Since each regions between neighboring surfaces can be integrated by using local surface topology, a proposed method is robust to registration errors and surface scanning noise. We also propose a method integrating of textures by using parameterization technique. We first transforms integrated surface into initial viewpoints of each surfaces. We then project each textures to transformed integrated surface. They will be then assigned into parameter domain for integrated surface and be integrated according to the seaming lines for surfaces. Experimental results show that the proposed method is efficient to face modeling.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.494-499
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• 2012

In this paper, a new method for detecting various objects that can be risks to safety navigation in sea environment is proposed. By analysing Infrared(IR) images obtained from various sea environments, we could find out that object regions include both horizontal and vertical direction edges while background regions of sea surface mainly include vertical direction edges. Therefore, we present an approach to detecting object regions considering horizontal and vertical edges. To this end, in the first step, image enhancement is performed by suppressing noises such as sea glint and complex clutters using a statistical filter. In the second step, a horizontal edge map and a vertical edge map are generated by 1-D Discrete Cosine Transform technique. Then, a combined map integrating the horizontal and the vertical edge maps is generated. In the third step, candidate object regions are detected by a adaptive thresholding method. Finally, exact object regions are extracted by eliminating background and clutter regions based on morphological operation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.85-94
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• 2004

Object tracking in a real time image is one of interesting subjects in computer vision and many Practical application fields during the past couple of years. But sometimes existing systems cannot find all objects by recognizing background noise as object. This paper proposes a method of object detection and tracking using adaptive background image in real time. To detect object which is not influenced by illumination and to remove noise in background image, this system generates adaptive background image by real time background image updating. This system detects object using the difference between background image and input image from camera. After setting up Minimum Bounding Rectangle(MBR) using the internal point of detected object, the system tracks object through this MBR In addition, this paper evaluates the test result about performance of proposed method as compared with existing tracking algorithm.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.23-26
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• 2019

본 논문에서는 X-Ray 영상에서 용접한 부분의 기공이나 균열 등의 결함 영역을 추출하는 새로운 방법을 제안한다. 제안된 방법은 세라믹 X-Ray 영상에서 비등방성 확산 필터를 적용하여 영상의 잡음을 제거하고, 수직 및 수평 히스토그램을 각각 적용하여 용접 영역을 추출한 후, 최소 자승법을 적용하여 배경 밝기를 제거하고, 사다리꼴 형태의 Fuzzy Stretching기법을 적용하여 명암 값을 강조하여 결함 영역과 그 외의 영역간의 명암 대비를 강조한다. 그리고 Fuzzy C_Means 알고리즘을 적용하여 결함 영역을 세분화한 후, Fuzzy C_Means을 적용하여 생성된 클러스터들의 중심 명암 값을 이용하여 ${\alpha}_-cut$을 설정한 후에 임계구간을 구하고 영상을 이진화하여 최종적으로 결함 영역을 추출한다. 제안된 방법의 결함 추출 성능을 확인하기 위하여 세라믹 X-Ray 영상을 대상으로 실험한 결과, 기존의 방법보다 결함 영역이 정확히 추출되는 것을 확인할 수 있었다.