• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.2
• /
• pp.213-218
• /
• 2013

In this paper, a video based ship detection method is proposed to monitor port efficiently. Visual saliency map algorithm and mean shift algorithm is applied to detect moving ships don't include background information which is difficult to track moving ships. It is easy to detect ships at the port using saliency map algorithm, because it is very effective to extract saliency object from background. To remove background information in the saliency region, image segmentation and clustering using mean shift algorithm is used. As results of detecting simulation with images of a camera installed at the harbor, it is shown that the proposed method is effective to detect ships.

• Journal of IKEEE
• /
• v.6 no.1 s.10
• /
• pp.54-64
• /
• 2002

In this paper, we propose the algorithm for segmenting the moving speaker and tracking its movement in the video conference image. For real time processing, we simplify the algorithm which is processed in the order of the segmenting and the tracking step. In the segmenting step, the speaker object is segmented from the image by using both the motion information obtained from the difference method and the illuminance information of image. The reference mask image is created from segmented speaker object. In the tracking step, the moving speaker is tracked by using simple block matching algorithm of which computation time is reduced by discarding the blocks which are classified into the unuseful blocks. In the simulation, we can get the good result of segmenting and tracking the moving speaker by applying the proposed algorithm to several test images.

• International Journal of Contents
• /
• v.11 no.2
• /
• pp.15-19
• /
• 2015

In this paper, we propose an efficient document layout analysis algorithm that includes table detection. Typical methods of document layout analysis use the height and gap between words or columns. To correspond to the various styles and sizes of documents, we propose an algorithm that uses the mean value of the distance transform representing thickness and compare with components in the local area. With this algorithm, we combine a table detection algorithm using the same feature as that of the text classifier. Table candidates, separators, and big components are isolated from the image using Connected Component Analysis (CCA) and distance transform. The key idea of text classification is that the characteristics of the text parallel components that have a similar thickness and height. In order to estimate local similarity, we detect a text region using an adaptive searching window size. An improved adaptive run-length smoothing algorithm (ARLSA) was proposed to create the proper boundary of a text zone and non-text zone. Results from experiments on the ICDAR2009 page segmentation competition test set and our dataset demonstrate the superiority of our dataset through f-measure comparison with other algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.1 no.1
• /
• pp.10-16
• /
• 2002

In this paper, a novel algorithm for segmentation of moving multiple vehicles in video sequences using logic operations is proposed. For the case of multiple vehicles in a scene, the proposed algorithm begins with a robust double-edge image derived from the difference between two successive frames using exclusive OR operation. After extracting only the edges of moving multiple vehicles using Laplacian filter, AND operation and dilation operation, the image is segmented into moving multiple vehicle image. The features of moving vehicles can be directly extracted from the segmented images. The proposed algorithm has no the two preprocessing steps, so it can reduce noises which are norm at in preprocessing of the original images. The algorithm is more simplified using logic operations. The proposed algorithm is evaluated on an outdoor video sequence with moving multiple vehicles in 90,000 frames of 30fps by a low-end video camera and produces promising results.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.7
• /
• pp.149-156
• /
• 2011

This paper proposes the effective edge selection algorithm for the rapid processing time and low memory usage of efficient graph-based image segmentation on mobile device. The graph-based image segmentation algorithm is to extract objects from a single image. The objects are consisting of graph edges, which are created by information of each image's pixel. The edge of graph is created by the difference of color intensity between the pixel and neighborhood pixels. The object regions are found by connecting the edges, based on color intensity and threshold value. Therefore, the number of edges decides on the processing time and amount of memory usage of graph-based image segmentation. Comparing to personal computer, the mobile device has many limitations such as processor speed and amount of memory. Additionally, the response time of application is an issue of mobile device programming. The image processing on mobile device should offer the reasonable response time, so that, the image segmentation processing on mobile should provide with the rapid processing time and low memory usage. In this paper, we demonstrate the performance of the effective edge selection algorithm, which effectively controls the edges of graph for the rapid processing time and low memory usage of graph-based image segmentation on mobile device.

• Journal of KIISE:Software and Applications
• /
• v.32 no.2
• /
• pp.128-139
• /
• 2005

Moving object boundary is very important for moving object segmentation. But the moving object boundary shows broken boundary We invent a novel space-oriented boundary linking algorithm to link the broken boundary The boundary linking algorithm forms a quadrant around the terminating pixel in the broken boundary and searches forward other terminating pixel to link within a radius. The boundary linking algorithm guarantees shortest distance linking. We also register the background from image sequence. We construct two object masks, one from the result of boundary linking and the other from the registered background, and use these two complementary object masks together for moving object segmentation. We also suppress the moving cast shadow using Roberts gradient operator. The major advantages of the proposed algorithms are more accurate moving object segmentation and the segmentation of the object which has holes in its region using these two object masks. We experiment the algorithms using the standard MPEG-4 test sequences and real video sequence. The proposed algorithms are very efficient and can process QCIF image more than 48 fps and CIF image more than 19 fps using a 2.0GHz Pentium-4 computer.

• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10a
• /
• pp.178-182
• /
• 1988

In this study, the motion compensating interpolation algorithm is presented. The presented algorithm allows the unblutted reconstruction of omitted frames. It is shown that the Walker & Rao's estimation algorithm using modified displaced frame difference combined with rectangulat adaptive measurement window increases the reliability of the estimation results. The remark ably improved image quality is achieved by change detection and segmentation.

• 연구논문집
• /
• s.25
• /
• pp.147-154
• /
• 1995

In this paper, we discussed the convergence and the properties of an iterative algorithm method in order to improve a bimean clustering algorithm. This algorithm that we have discussed choose automatically an optimum threshold as a result of an iterative process, successive iterations providing increasingly cleaner extractions of the object region, The iterative approach of a proposed algorithm is seen to select an appropriate threshold for the low contrast images.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.43 no.2 s.308
• /
• pp.21-32
• /
• 2006

The license plate recognition (LPR) unit consists of the following core components: plate region segmentation, individual character extraction, and character recognition. Out of the above three components, accuracy in the performance of plate region segmentation determines the overall recognition rate of the LPR unit. This paper proposes an algorithm for segmenting the license plate region on the front or rear of a vehicle in a fast and accurate manner. In the case of the proposed algorithm images are captured on the spot where unmanned monitoring of illegal parking and stowage is performed with a variety of roadway environments taken into account. As a means of enhancing the segmentation performance of the on-the-spot-captured images of license plate regions, the proposed algorithm uses a mathematical model for license plate colors to convert color images into digital data. In addition, this algorithm uses Gaussian smoothing and double threshold to eliminate image noises, one-pass boundary tracing to do region labeling, and MBR to determine license plate region candidates and extract individual characters from the determined license plate region candidates, thereby segmenting the license plate region on the front or rear of a vehicle through a verification process. This study contributed to addressing the inability of conventional techniques to segment the license plate region on the front or rear of a vehicle where the frame of the license plate is damaged, through processing images in a real-time manner, thereby allowing for the practical application of the proposed algorithm.

• Journal of Korea Multimedia Society
• /
• v.17 no.3
• /
• pp.342-352
• /
• 2014

This paper proposes an automatic segmentation method of cortical bone and trabecular bone and describes an implementation of structural analysis method of trabecular bone in micro-CT images. The proposed segmentation method extract bone region with binarization using a threshold value. Next, it finds adjacent contour lines from outer boundary line into inward direction and sets candidate regions of cortical bone. Next it remove cortical bone region by finding the candidate cortical region of which the average pixel value is maximum. We implemented the method which computes four structural indicators BV/TV, Tb.Th, Tb.Sp, Tb.N by using VTK(Visualization ToolKit) and sphere fitting algorithm. We applied the implemented method to twenty proximal femur of mouses and compared with the manual segmentation method. Experimental result shows that the average error rates between the proposed segmentation method and the manual segmentation method are less than 3% for the four structural indicatiors. This result means that the proposed method can be used instead of the combersome and time consuming manual segmentation method.