• Structural Engineering and Mechanics
• /
• v.57 no.4
• /
• pp.587-602
• /
• 2016

In structural reliability analysis, the response surface method is widely adopted because of its numerical efficiency. It should be understood that the response function must approximate the actual limit state function accurately in the main region influencing failure probability where it is evaluated. However, the size of main region influencing failure probability was not defined clearly in current response surface methods. In this study, the concept of sub-region of interest is constructed, and an improved response surface method is proposed based on the sub-region of interest. The sub-region of interest can clearly define the size of main region influencing failure probability, so that the accuracy of the evaluation of failure probability is increased. Some examples are introduced to demonstrate the efficiency and the accuracy of the proposed method for both numerical and implicit limit state functions.

• Proceedings of the IEEK Conference
• /
• 2000.07b
• /
• pp.927-930
• /
• 2000

Visual features of lip area play an important role in the visual speech information. We are concerned about correct lip area as region of interest (ROI). In this paper, we propose a robust and fast method for locating the mouth corners. Also, we define a region of interest at mouth during speech. A method, which we have used, only uses the horizontal and vertical image operators at mouth area. This searching is performed by fitting the ROI-template to image with illumination control. Most of the lip extraction algorithms are dependent on luminosity of image. We just used the binary image where the variable threshold is applied. The variable threshold varies to illumination condition. In order to control those variations, the gray-tone is converted to binary image by threshold, which is obtained through Multiple Linear Regression Analysis (MLRA) about divided 2D special region. Thus we obtained the region of interest at mouth area, which is the robust extraction about illumination. A region of interest is automatically extracted.

• Proceedings of the IEEK Conference
• /
• 2002.06c
• /
• pp.207-210
• /
• 2002

In this paper, content-based retrieval for region of interest(ROI) has been described, using maximum bin color. From a given query image, the object of interest is selected by a user. Using maximum bin color of the selected object, candidate regions are extracted from database images. The final regions of interest are determined by comparing the normalized histograms of the selected object and each candidate region.

• Journal of the Korean Statistical Society
• /
• v.9 no.2
• /
• pp.145-172
• /
• 1980

Draper and Lawrence (1965a) have given mixture designs for three factors when all the mixture components can vary on the entire factor space so that the region of interest is an equilateral triangle in two dimensions. In this paper their work is extended to the cases when the region of interest is an echelon, parallelogram, pentagon or hexagon, because of the restirctions imposed on some or all of the mixture components. The principles used in the choice of appropriate designs are those originally introduced by Box and Draper(1959). It is assumed that a response surface equation of first order is fitted, but there is a possibility of bias error due to presence of second order terms in the true model. Minimum bias designs for several cases of restricted regions of interest are illustrated.

• Journal of Cadastre & Land InformatiX
• /
• v.49 no.1
• /
• pp.103-112
• /
• 2019

Extraction of region of interest for satellite image classification is one of the important techniques for efficient management of the national land space. However, recent studies on satellite image classification often depend on the information of the selected image in selecting the region of interest. This study propose an effective method of selecting the area of interest using the continuous digital topographic map constructed from high resolution images. The spatial information used in this research is based on the digital topographic map from 2013 to 2017 provided by the National Geographical Information Institute and the 2015 Sejong City land cover map provided by the Ministry of Environment. To verify the accuracy of the extracted area of interest, KOMPSAT-3A satellite images were used which taken on October 28, 2018 and July 7, 2018. The baseline samples for 2015 were extracted using the unchanged area of the continuous digital topographic map for 2013-2015 and the land cover map for 2015, and also extracted the baseline samples in 2018 using the unchanged area of the continuous digital topographic map for 2015-2017 and the land cover map for 2015. The redundant areas that occurred when merging continuous digital topographic maps and land cover maps were removed to prevent confusion of data. Finally, the checkpoints are generated within the region of interest, and the accuracy of the region of interest extracted from the K3A satellite images and the error matrix in 2015 and 2018 is shown, and the accuracy is approximately 93% and 72%, respectively. The accuracy of the region of interest can be used as a region of interest, and the misclassified region can be used as a reference for change detection.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.3
• /
• pp.117-122
• /
• 2023

Gaze estimation, which automatically recognizes where a user is currently staring, and object detection based on estimated gaze point, can be a more accurate and efficient way to understand human visual behavior. in this paper, we propose a method to detect the objects within the region of interest around the gaze point. Specifically, after estimating the 3D gaze point, a region of interest based on the estimated gaze point is created to ensure that object detection occurs only within the region of interest. In our experiments, we compared the performance of general object detection, and the proposed object detection based on region of interest, and found that the processing time per frame was 1.4ms and 1.1ms, respectively, indicating that the proposed method was faster in terms of processing speed.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.4
• /
• pp.189-198
• /
• 2024

Lipreading is one of the important parts of speech recognition, and several studies have been conducted to improve the performance of lipreading in lipreading systems for speech recognition. Recent studies have used method to modify the model architecture of lipreading system to improve recognition performance. Unlike previous research that improve recognition performance by modifying model architecture, we aim to improve recognition performance without any change in model architecture. In order to improve the recognition performance without modifying the model architecture, we refer to the cues used in human lipreading and set other regions such as chin and cheeks as regions of interest along with the lip region, which is the existing region of interest of lipreading systems, and compare the recognition rate of each region of interest to propose the highest performing region of interest In addition, assuming that the difference in normalization results caused by the difference in interpolation method during the process of normalizing the size of the region of interest affects the recognition performance, we interpolate the same region of interest using nearest neighbor interpolation, bilinear interpolation, and bicubic interpolation, and compare the recognition rate of each interpolation method to propose the best performing interpolation method. Each region of interest was detected by training an object detection neural network, and dynamic time warping templates were generated by normalizing each region of interest, extracting and combining features, and mapping the dimensionality reduction of the combined features into a low-dimensional space. The recognition rate was evaluated by comparing the distance between the generated dynamic time warping templates and the data mapped to the low-dimensional space. In the comparison of regions of interest, the result of the region of interest containing only the lip region showed an average recognition rate of 97.36%, which is 3.44% higher than the average recognition rate of 93.92% in the previous study, and in the comparison of interpolation methods, the bilinear interpolation method performed 97.36%, which is 14.65% higher than the nearest neighbor interpolation method and 5.55% higher than the bicubic interpolation method. The code used in this study can be found a https://github.com/haraisi2/Lipreading-Systems.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.8
• /
• pp.1843-1859
• /
• 2013

The continuous increase of the spatial resolution of remote sensing images brings great challenge to image analysis and processing. Traditional prior knowledge-based region detection and target recognition algorithms for processing high resolution remote sensing images generally employ a global searching solution, which results in prohibitive computational complexity. In this paper, a more efficient region of interest (ROI) detection algorithm based on visual attention and threshold segmentation (VA-TS) is proposed, wherein a visual attention mechanism is used to eliminate image segmentation and feature detection to the entire image. The input image is subsampled to decrease the amount of data and the discrete moment transform (DMT) feature is extracted to provide a finer description of the edges. The feature maps are combined with weights according to the amount of the "strong points" and the "salient points". A threshold segmentation strategy is employed to obtain more accurate region of interest shape information with the very low computational complexity. Experimental statistics have shown that the proposed algorithm is computational efficient and provide more visually accurate detection results. The calculation time is only about 0.7% of the traditional Itti's model.

• Journal of Broadcast Engineering
• /
• v.7 no.4
• /
• pp.335-344
• /
• 2002

A sub-picture slice structure is proposed which can perform the region-of-interest coding effectively, where the subjective quality can be improved by coding the region-of-interest in higher quality than the background region. In addition, the bit allocation mechanism is Proposed where the interval between quantization parameters of the foreground and background region is fixed. And the method to reduce the boundary effect between the foreground and background region is proposed. The foreground region is better protected to the network channel error than the background region. which results in the overall subjective quality improvement in the error prone environments.

• Proceedings of the KIEE Conference
• /
• 2006.10c
• /
• pp.297-299
• /
• 2006

Searching the region of interest on the Hough transform domain is done to determine the real road boundary on the high speed way. The mathematical morphology is employed to obtain the gradient image which is utilized in Hough transform. Many possible candidates of lines could appear on the ordinary road environment and simple selection of the strongest line segments likely to be fault boundary lines. To solve such problem, the search area for the candidates of the road boundary which is called the region of interest is limited on the Hough space. The effectiveness of the proposed algorithm has been shown with experimental results.