• Journal of Biomedical Engineering Research
• /
• v.10 no.3
• /
• pp.331-342
• /
• 1989

This paper presents a new algorithm that extracts lung region in X-Rays and enhance.j the region. Comparing to prior algorithms that enhance whole X-Ray image, this algorithm leads more effective results. For this algorithm extracts lung region first, and enhances the lung region excluding parameters of other region. For choosing optimal threshold, we compare OTSU's mothod with the proposed method. We obtain lung boundary using contour following algorithm and Rray level searching method in gray level rescaled image. We Process histogram equalization in lung region and obtain enhanced lung image. By using the proposed algorithm, we obtain lung region effectively in chest X-Ray that need in medical image diagnostic system.

• Journal of Korea Multimedia Society
• /
• v.7 no.3
• /
• pp.319-326
• /
• 2004

In this paper, we propose color image segmentation by region merging method preserving the boundary of an object. The proposed method selects initial region by using quantized image's index map after vector quantizing an original image. After then, we merge regions by applying boundary restricted factor in order to consider the boundary of an object in HSI color space. Also we merge the regions in RGB color space for non-processed regions in HSI color space. And we reduce processing time by decreasing iterative process in region merging algorithm. Experimental results have demonstrated the superiority in region's segmentation results and processing time for various images.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.6
• /
• pp.76-86
• /
• 1999

In this paper, it is shown that the car number plate are segmented and extracted more efficiently by using wavelet transform. A car image is decomposed by wavelet transform, and the high frequency image of the decomposed image are selected as feature images. Three selected feature images are synthesized of a single feature image, and a region including the plate is segmented by the correlation coefficient between the feature image and the synthesized image. For segmented plate region, the car plate region is extracted by deciding the Y-axis region composed by vertical region, the car plate region is extracted by deciding the Y-axis region composed by vertical histogram and the X-axis region composed by the variance histogram. Some experiment results of the various image and shown. It has been shown from the results with the high rate of 96% that the car number plates can be segmented and extracted more extractly and efficiently than converntional method.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.810-813
• /
• 2004

Indexing and Retrieving images from large and varied collections using image content as a key is a challenging and important problem in computer vision application. In this paper, a color Content-based Image Retrieval (CBIR) system using hierarchical Region of Interest (ROI) query and indexing is presented. During indexing process, First, The ROIs on every image in the image database are extracted using a region-based image segmentation technique, The JSEG approach is selected to handle this problem in order to create color-texture regions. Then, Color features in form of histogram and correlogram are then extracted from each segmented regions. Finally, The features are stored in the database as the key to retrieve the relevant images. As in the retrieval system, users are allowed to select ROI directly over the sample or user's submission image and the query process then focuses on the content of the selected ROI in order to find those images containing similar regions from the database. The hierarchical region-of-interest query is performed to retrieve the similar images. Two-level search is exploited in this paper. In the first level, the most important regions, usually the large regions at the center of user's query, are used to retrieve images having similar regions using static search. This ensures that we can retrieve all the images having the most important regions. In the second level, all the remaining regions in user's query are used to search from all the retrieved images obtained from the first level. The experimental results using the indexing technique show good retrieval performance over a variety of image collections, also great reduction in the amount of searching time.

• Proceedings of the IEEK Conference
• /
• 2004.08c
• /
• pp.814-818
• /
• 2004

Off-line handwritten character recognition is in difficulty of incomplete preprocessing because it has not dynamic and timing information besides has various handwriting, extreme overlap of the consonant and vowel and many error image of stroke. Consequently off-line handwritten character recognition needs to study about preprocessing of various methods such as binarization and thinning. This paper considers running time of watershed algorithm and the quality of resulting image as preprocessing For off-line handwritten Korean character recognition. So it proposes application of effective watershed algorithm for segmentation of character region and background region in gray level character image and segmentation function for binarization image and segmentation function for binarization by extracted watershed image. Besides it proposes thinning methods which effectively extracts skeleton through conditional test mask considering running time and quality. of skeleton, estimates efficiency of existing methods and this paper's methods as running time and quality. Watershed image conversion uses prewitt operator for gradient image conversion, extracts local minima considering 8-neighborhood pixel. And methods by using difference of mean value is used in region merging step, Converted watershed image by means of this methods separates effectively character region and background region applying to segmentation function. Average execution time on the previous method was 2.16 second and on this paper method was 1.72 second. We prove that this paper's method removed noise effectively with overlap stroke as compared with the previous method.

• The KIPS Transactions:PartB
• /
• v.9B no.3
• /
• pp.311-318
• /
• 2002

Document image layout analysis contains the process to segment document image into detailed regions and the process to classify the segmented regions into text, picture, table or etc. In the region classification process, the size of a region, the density of black pixels, and the complexity of pixel distribution are the bases of region classification. But in case of picture, the ranges of these bases are so wide that it's difficult to decide the classification threshold between picture and others. As a result, the picture has a higher region classification error than others. In this paper, we propose document image layout analysis method which has a better performance for the picture and text region classification than that of previous methods including commercial softwares. In the picture and text region classification, median filter is used in order to reduce the influence of the size of a region, the density of black pixels, and the complexity of pixel distribution. Futhermore the classification error is corrected by the use of region expanding filter and constrained conditions.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.181-183
• /
• 2004

In this paper, We proposed an algorithm which extraction iris region from 2D image. Our method is composed of three parts : internal boundary defection and external boundary detection. Since eyelid and eyelash cover part of the boundary and the size of iris changes continuously, it is difficult to extract iris region accurately. For the interior and exterior boundary detection, we used partial differentiation of histogram. Performance of the proposed algorithm is tested and evaluated using 360 iris image samples.

• The Journal of Information Technology
• /
• v.10 no.3
• /
• pp.15-31
• /
• 2007

Region-of-Interest is the region within the image selected for the users needs. The development of multimedia has made the expectation of image telecommunication higher, but the usage of the image, image transmission time, and image storage create problems. When transmitter or the receiver stops transmission at some point, we can still see the general image and the ROI maintains better image quality if the ROI is specified beforehand. In this paper, three methods are proposed and constructed for the transmission of ROI. In the first method, the ROI and the background are separated and then encoded as described above. The second method is to encode without separating the ROI and the background. The masked region is scaled and the coefficients are increased, then the region is transmitted first. The third method is the loseless coding of the ROI. For loseless coding, real number tap cannot be restored perfectly due to the rounding error, so the method of using integers is used. The proposed method shows a better performance than EZW even in case of ROI's PSNR at quality of 40 dB.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2012.05a
• /
• pp.40-42
• /
• 2012

Colorization is a method using computer to add color to a black and white image automatically. The input is a grayscale image and some representative pixels (RPs). The RPs contain the color information for the image, and it indicates each region's color information. Colorization-based coding is a novel way for lossy image compression, it decodes a color image to get grayscale image and extracts RPs from the image. Because RPs decides the region's color and we also want small data size for image compression, form this viewpoint the paper proposes a way to get better and fewer RPs based on watershed segmentation. According to the segmentation result we also improve the original chrominance blending colorization method to save decode time and get better reconstruct image.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.28 no.2
• /
• pp.243-251
• /
• 2004

This study was interested in examining the image of a co-brand with the case of＇CHIMERIC＇, the co-brand of Daegu city in Korea. The purpose of the study was to investigate the difference in brand image by brand knowledge and the effects of brand image on brand preference, brand purchase, and brand satisfaction. A total of 354 questionnaires collected from the region(Daegu)＇s residents, who were aware of CHIMERIC, were analyzed. Factor analysis extracted 6 factors of brand image including symbolic image, product, ad, price, distribution, and publicity. The results revealed that there were differences in product and publicity images by brand knowledge. Symbolic and publicity images and brand knowledge affected brand preference, which in turn had the strongest effect on brand purchase. Brand knowledge also affected brand purchase while no direct effect of brand image was observed. Brand satisfaction was affected by brand preference, publicity, and ad image.