• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2982-2988
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• 2014

The edge detection is a pre-processing of such as image segmentation, image recognition, etc, and many related studies are being conducted both in domestic and abroad. Representative edge detection methods are Sobel, Prewitt, Laplacian, Roberts and Canny edge detectors. Such existing methods are possible for superb detections of edges if edges are detected from videos without noises. However, for video degraded by the salt-and-pepper noise, the edge detection characteristic is shown to be insufficient due to the noise influence. Therefore, in this study, the area is separated as the top, down, left and right from the mask's center pixel first to acquire a superb edge detection characteristic from the video damaged by the salt-and-pepper noise. And the algorithm that detects the final edge by applying the directional mask on the assumed factor of mask that is obtained according to the result of determination for the noise status of representative pixel value of each area.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.50-57
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• 2005

We present a simple and effective method of face and facial feature detection under pose variation of user face in complex background for the human-robot interaction. Our approach is a flexible method that can be performed in both color and gray facial image and is also feasible for detecting facial features in quasi real-time. Based on the characteristics of the intensity of neighborhood area of facial features, new directional template for facial feature is defined. From applying this template to input facial image, novel edge-like blob map (EBM) with multiple intensity strengths is constructed. Regardless of color information of input image, using this map and conditions for facial characteristics, we show that the locations of face and its features - i.e., two eyes and a mouth-can be successfully estimated. Without the information of facial area boundary, final candidate face region is determined by both obtained locations of facial features and weighted correlation values with standard facial templates. Experimental results from many color images and well-known gray level face database images authorize the usefulness of proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.21 no.4
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• pp.9-15
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• 2016

Symmetry is everywhere in the world around us from galaxy to microbes. From ancient times symmetry is considered to be a reflection of the harmony of universe. Symmetry is not only a significant clue for human cognitive process, but also useful information for computer vision such as image understanding system. Application areas include face detection and recognition, indexing of image database, image segmentation and detection, analysis of medical images, and so on. The technique used in this paper extracts edges, and the perpendicular bisector of any two edge points is considered to be a candidate axis of symmetry. The coefficients of candidate axis are accumulated in the coefficient space. Then the axis of symmetry is determined to be the line for which the coefficient histogram has maximum value. In this paper, an improved method is proposed that utilizes the directional information of edges, which is a byproduct of the edge detection process. Experiment on 20 test images shows that the proposed method performs 22.7 times faster than the original method. In another test on 5 images with 4% salt-and-pepper noise, the proposed method detects the symmetry successfully, while the original method fails. This result reveals that the proposed method enhances the speed and accuracy of detection process at the same time.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.766-772
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• 2015

This paper proposes an object detection method based on motion estimation using background subtraction in the fisheye images obtained through omni-directional camera mounted on the vehicle. Recently, most of the vehicles installed with rear camera as a standard option, as well as various camera systems for safety. However, differently from the conventional object detection using the image obtained from the camera, the embedded system installed in the vehicle is difficult to apply a complicated algorithm because of its inherent low processing performance. In general, the embedded system needs system-dependent algorithm because it has lower processing performance than the computer. In this paper, the location of object is estimated from the information of object's motion obtained by applying a background subtraction method which compares the previous frames with the current ones. The real-time detection performance of the proposed method for object detection is verified experimentally on embedded board by comparing the proposed algorithm with the object detection based on LKOF (Lucas-Kanade optical flow).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.79-84
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• 2005

In this paper, we developed an omni-directional surveillance and motion detection method. The fish-eye lens provides a wide field of view image. Using this image, the equi-distance model for the fish-eye lens is applied to get the perspective and panorama images. Generally, we must consider the trade-off between resolution and field of view of an image from a camera. To enhance the resolution of the result images, some kind of interpolation methods are applied. Also the moving edge method is used to detect moving objects for the object tracking.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1395-1403
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• 2022

Lately, over 4K high definition and high dynamic range (HDR) display devices are popularized, various interpolation and HDR methods have been researched to expand the size and the dynamic range. Since most of the legacy low resolution (LR) images require both an interpolation and a HDR tone mapping methods, the two processes should be subsequently applied. Therefore, the proposed algorithm presents a HDR up-scaling algorithm using undecimated wavelet transform and Retinex method, which transfers a LR image of low dynamic range (LDR) into the high resolution (HR) with HDR. The proposed algorithm consists of an up-scaling scheme increasing the image size and a tone mapping scheme expanding the dynamic range. The up-scaling scheme uses the undecimated version of the simplest Haar wavelet analysis for the 8-directional interpolation and the change region is extracted during the analysis. This region information is utilized in controlling the surround functions' size of the proposed tone mapping using MSRCR, to enhance the pixels of around the edges that are dominant feature of the subjective image quality. As the results, the proposed algorithm can apply an up-scaling and tone mapping processes in accordance with the type of pixel.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.497-502
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• 2003

Content-based video copy detection is a complementary approach to watermarking. As opposed to watermarking, which relies on inserting a distinct pattern into the video stream, video copy detection techniques match content-based signatures to detect copies of video. Existing typical content-based copy detection schemes have relied on image matching which is based on key frame detection. This paper proposes a motion directional histogram, which is quantized and accumulated the direction of motion, for video copy detection. The video clip is represented by a motion directional histogram as a 1-dimensional graph. This method is suitable for real time indexing and counting the TV CF verification that is high motion video clips.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.1
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• pp.7-12
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• 2009

In this paper, we propose a directional feature extraction method for off-line handwritten numerals by using the morphological operations. Direction features are obtained from four directional line images, each of which contains horizontal, vertical, right-diagonal and left-diagonal lines in entire numeral lines. Conventional method for extracting directional features uses Kirsch masks which generate edge-shaped double line images for each direction, whereas our method uses directional erosion operations and generate single line images for each direction. To apply these directional erosion operations to the numeral image, preprocessing steps such as thinning and dilation are required, but resultant directional lines are more similar to numeral lines themselves. Our four [$4{\times}4$] directional features of a numeral are obtained from four directional line images through a zoning method. For obtaining the higher recognition rates of the handwrittern numerals, we use the multiple feature which is comprised of our proposed feature and the conventional features of a kirsch directional feature and a concavity feature. For recognition test with given features, we use a multi-layer perceptron neural network classifier which is trained with the back propagation algorithm. Through the experiments with the CENPARMI numeral database of Concordia University, we have achieved a recognition rate of 98.35%.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.939-946
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• 2018

In this paper, we implement a viewer program that can monitor effectively using omni-directional images. The program consists of four modes: Normal mode, ROI(Region of Interest) mode, Tracking mode, and Auto-rotation mode, and the results for each mode is displayed simultaneously. In the normal mode, the wide angle image is rendered as a spherical image to enable pan, tilt, and zoom. In ROI mode, the area is displayed expanded by selecting an area. And, in Auto-rotation mode, it is possible to track the object by mapping the position of the object with the rotation angle of the spherical image to prevent the object from deviating from the spherical image in Tracking mode. Parallel programming for processing of multiple modes is performed to improve the processing speed. This has the advantage that various angles can be seen compared with surveillance system having a limited angle of view.

• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.41-46
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• 2021

The method of the edge detection algorithm based on grayscale mathematical morphology has the advantage that image noise can be removed and processed in parallel, and the operation speed is fast. However, the method of detecting the edge of an image using a single structural scale element may be affected by image information. The characteristics of grayscale morphology may be limited to the edge information result of the operation result by repeatedly performing expansion, erosion, opening, and containment operations by repeating structural elements. In this paper, we propose an edge detection algorithm that applies a structural element with strong directionality to noise and then applies weighted entropy to each pixel information in the element. The result of applying the multi-scale structural element applied to the image and the result of applying the directional weighted entropy were compared and analyzed, and the simulation result showed that the proposed algorithm is superior in edge detection.