• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1613-1631
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• 2011

Several metrics have been reported in the literature to assess stereo image quality, mostly based on visual attention or human visual sensitivity based distortion prediction with the help of disparity information, which do not consider the combined aspects of human visual processing. In this paper, visual attention and depth assisted stereo image quality assessment model (VAD-SIQAM) is devised that consists of three main components, i.e., stereo attention predictor (SAP), depth variation (DV), and stereo distortion predictor (SDP). Visual attention is modeled based on entropy and inverse contrast to detect regions or objects of interest/attention. Depth variation is fused into the attention probability to account for the amount of changed depth in distorted stereo images. Finally, the stereo distortion predictor is designed by integrating distortion probability, which is based on low-level human visual system (HVS), responses into actual attention probabilities. The results show that regions of attention are detected among the visually significant distortions in the stereo image pair. Drawbacks of human visual sensitivity based picture quality metrics are alleviated by integrating visual attention and depth information. We also show that positive correlation with ground-truth attention and depth maps are increased by up to 0.949 and 0.936 in terms of the Pearson and the Spearman correlation coefficients, respectively.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.36-40
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• 1996

There are two prevailing techniques, mechanical and optical profilometers, to measure 3-dimensional configurations of the human skin furrows. The methods have some limitations such as, accuracies or resolutions of the acquired 3-dimensional data and consistencies according to the repeated experiments. We devised an optical profilometer that is called stereo image optical profilometer (SOP) based on stereo image processing techniques. A stereo image is a pair of images that obtained from two cameras which have different angles. From the digital stereo images, the clinical informations for skin can be obtained by some signal processing techniques. In this paper, we focused on the 3-dimensional graphical visualizations of the structures and state of the skin furrows by solving the corresponding problem from the left and right pairs of the stereo images.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.198-204
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• 2012

Tracking and recognition of robots are required for the cooperation task of robots in various environments. In the paper, a tracking control system of moving robot using stereo image processing, code-book model and fuzzy controller is proposed. First, foreground and background images are separated by using code-book model method. A candidate region is selected based on the color information in the separated foreground image and real distance of the robot is estimated from matching process of depth image that is acquired through stereo image processing. The open and close processing of image are applied and labeling according to the size of mobile robot is used to recognize the moving robot effectively. A fuzzy tracking controller using distance information and mobile information by stereo image processing is designed for effective tracking according to the movement velocity of the target robot. The proposed fuzzy tracking control method is verified through tracking experiments of mobile robots with stereo camera.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.7
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• pp.509-516
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• 2004

This paper proposes an image processing algorithm for detecting obstacles on road using DLI(disparity of lane-related information) that is generated by stereo images acquired from dual cameras mounted on a moving vehicle. The DLI is a disparity that is acquired using a single lane information from road lane detection. For the purpose to reduce processing time, we use small block of edge-histogram based blocking logic. This algorithm detects moving objects such as preceding vehicles and obstacles. The proposed algorithm has been implemented in a personal computer with the road image data of a typical highway. We successfully performed experiments under a wide variety of road conditions without changing parameter values or adding human intervention. Experimental results also showed that the proposed DLI is quite successful.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.10a
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• pp.147-152
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• 1997

This paper presents a method for measuring and analyzing strains in sheet metal forming by stereo vision system. A better understanding and evaluation of the formability can be achieved by analyzing stain distribution in deformed sheet metals. By means of image processing technique, it is possible to get strain distribution efficiently. For measuring strain automatically and accurately, algorithms for camera calibration, grid detection, stereo matching and strain analysis has been developed and verified by experiments with GUI(Graphic User Interface).

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.03a
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• pp.207-212
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• 1997

In estimating the formability of sheet metal, the stereo vision system contributes the accuracy of strain of sheet metal, the convenience in measuring the strain of sheet metal, and the handiness in preparing the forming limit diagram by calculating the 3D values and strain of sheet metal. The algorithm has been developed so that the 3D-coordinate values of sheet metal could be calculated by image processing which is composed of camera calibration, and the stereo matching of images in two viewpoints. By comparing with experiments, the possibility and the convenience of algorithm has been verified, which could calculate the 3D-coordinate values of sheet metal automatically by using the preprocessing of the original image of sheet metal, which had the noise before adjusting the camera calibration and the stereo matching algorithm.

• Journal of Multimedia Information System
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• v.9 no.3
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• pp.183-190
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• 2022

Image-based 3D object detection is one of the important and difficult problems in autonomous driving and robotics, and aims to find and represent the location, dimension and orientation of the object of interest. It generates three dimensional (3D) bounding boxes with only 2D images obtained from cameras, so there is no need for devices that provide accurate depth information such as LiDAR or Radar. Image-based methods can be divided into three main categories: monocular, stereo, and multi-view 3D object detection. In this paper, we investigate the recent state-of-the-art models of the above three categories. In the multi-view 3D object detection, which appeared together with the release of the new benchmark datasets, NuScenes and Waymo, we discuss the differences from the existing monocular and stereo methods. Also, we analyze their performance and discuss the advantages and disadvantages of them. Finally, we conclude the remaining challenges and a future direction in this field.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.293-293
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• 2010

In this paper, we propose a stereo vision based monitoring concept for passenger's safety on railroad platform. In general, basic concept of stereo image processing technique uses the correlations between left and right images, and extracts additional distance information. It provides easy removal of ambient illumination changes, which has been difficult to achieve with conventional 2D based image processing technique. In the paper, we present developed stereo camera and stereo vision based detection algorithm in order to monitor possible accidents at platform area, and verified the detection performance of proposed system with experimental results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1583-1590
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• 2011

As the existing radiation scanning systems use 2-dimensional radiation scanned images, the low accuracy has been pointed out as a problem of it. This research analyzes the applicability of the stereo image processing technique to X-ray scanned images. Two 2-dimensional radiation images which have different disparity values are acquired from a newly designed stereo image acquisition system which has one additional line sensor to the conventional system. Using a matching algorithm the 3D reconstruction process which find the correspondence between the images is progressed. As the radiation image is just a density information of the scanned object, the direct application of the general stereo image processing techniques to it is inefficient. To overcome this limitation of a stereo image processing in radiation area, we reconstruct 3-D shapes of the edges of the objects. Also, we proposed a new volume based 3D reconstruction algorithm. Experimental results show the proposed new volume based reconstruction technique can provide more efficient visualization for cargo inspection. The proposed technique can be used for such objects which CT or MRI cannot inspect due to restricted scan environment.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.178-182
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• 2007

This study represents the efficient depth measurement for 3-dimensional microsystems using the disparity histogram from stereo images. Implementation of user-friendly Windows program written in C++ involves the various methods for the stereo-image processing in which the minimization of matching-pixel error upon the unique point for stereo images was carried out as a pre-processing method. Even though MPC among various methods was adopted in the present measurement, the resulting measurements seem to require optimizations of the windows sizes and corrections of post-manipulation for stereo images. The present work using Windows program is promising to measure the 3-dimensional depth of micro-system efficiently in implementing the 3-dimensional structure of micro-systems.