• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4413-4425
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• 2020

In order to completely record all the information of realistic scenes, high dynamic range (HDR) images have been widely used in virtual reality, photography and computer graphics. A simple yet effective tone mapping method based on total variation is proposed so as to reproduce realistic scenes on low dynamic range (LDR) display devices. The structural component and texture component are obtained using total variation model in logarithmic domain. Then, the dynamic range of the structural component is compressed with an adaptive arcsine function. The texture component is processed by Taylor series. Finally, we adjust the saturation component using sigmoid function and restore the color information. Experimental results demonstrate that our method outperforms existing methods in terms of quality and speed.

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.933-943
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• 1997

In this paper, a conernt-based image retrival system with color assigments has been stueide and implment-ed. The color of images has been extracted after changing RGB color space to HSV(hue, saturation, value)that is the most compatible color for peop]e's feeling. In the color extracting, an image is divided into 9 different areasand 3 major colors for each area are selected by using color histograms. It is possible to chose the class of umages by keywords. We are evaluate four different types of queries such as an image input, keywords with color assignments, combining an image input and keywords with color assinments, and selecting specific part of an umage. Experimental rusults show that four different query types privide precision/recall 0.55/0.37, 0.57/0.43, 0.59/0.45 and 0.63/0.61, respectively. With color assignments, the retrieval system has been able to obtain high performance and validity.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.5
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• pp.111-120
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• 2016

Wire recognition is one of the important tasks in chip reverse engineering since connectivity comes from wires. Recognized wires are used to recover logical or functional representation of the corresponding circuit. Though manual recognition provides accurate results, it becomes impossible, as the number of wires is more than hundreds of thousands. Wires on a chip usually have specific intensity or color characteristics since they are made of specific materials. This paper proposes two stage wire recognition scheme; image binarization and then the process of determining whether regions in binary image are wires or not. We employ existing techniques for two processes. Since the second process requires the characteristics of wires, the users needs to select the typical wire region in the given image. The histogram characteristic of the selected region is used in calculating histogram similarity between the typical wire region and the other regions. The first experiment is to select the most appropriate binarization scheme for the second process. The second experiment on the second process compares three proposed methods employing histogram similarity of grayscale or HSV color since there have not been proposed any wire recognition method comparable by experiment. The best method shows more than 98% of true positive rate for 25 test examples.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.93-100
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• 2005

This study is to desist and implement an efficient microbial medical image retrieval system based on knowledge and content of them which can make use of more accurate decision on colony as doll as efficient education for new techicians. For this. re first address overall inference to set up flexible search path using rule-base in order U redure time required original microbial identification by searching the fastest path of microbial identification phase based on heuristics knowledge. Next, we propose a color ffature gfraction mtU, which is able to extract color feature vectors of visual contents from a inn microbial image based on especially bacteria image using HSV color model. In addition, for better retrieval performance based on large microbial databases, we present an integrated indexing technique that combines with B+-tree for indexing simple attributes, inverted file structure for text medical keywords list, and scan-based filtering method for high dimensional color feature vectors. Finally. the implemented system shows the possibility to manage and retrieve the complex microbial images using knowledge and visual contents itself effectively. We expect to decrease rapidly Loaming time for elementary technicians by tell organizing knowledge of clinical fields through proposed system.

• Journal of the Semiconductor & Display Technology
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• v.14 no.2
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• pp.29-34
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• 2015

Traffic lights are common in cities and are important cues for the path planning of intelligent vehicles. In this paper, we propose a robust and efficient algorithm for recognizing traffic lights from video sequences captured by a low cost off-the-shelf camera. Instead of using color information for recognizing traffic lights, a shape based approach is adopted. In learning and detection phase, Histogram of Oriented Gradients (HOG) feature is used and a cascade classifier based on Adaboost algorithm is adopted as the main classifier for locating traffic lights. To decide the color of the traffic light, a technique based on histogram analysis in HSV color space is utilized. Experimental results on several video sequences from typical urban environment prove the effectiveness of the proposed algorithm.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.48-52
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• 2023

From the past to the present, banners are consistently used as effective advertising means. In the case of Korea, there are frequent situations in which hidden advertisements are installed. As a result, such hidden advertisement materials may damage urban aesthetics and moreover, incur unnecessary manpower consumption and waste of money. The proposed method classifies the detected banners into good banner and bad banner. The classification results are based on whether the relevant banners are installed in compliance with legal guidelines. In the process, YOLO and Open Computer Vision library are used to determine from various perspectives whether banners in CCTV images comply with the guidelines. YOLO is used to detect the banner area in CCTV images, and OpenCV is used to detect the color values in the area for color comparison. If a banner is detected in the video, the proposed method calculates the location of the banner and the distance from the designated bulletin to determine whether it was installed within the designated location, and then compares whether the color used in the banner is complied with local government guidelines.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.57-63
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• 2009

The rapid growth of computer-based image database, necessity of a system that can manage an image information is increasing. This paper presents a region-based image retrieval method using the combination of color(autocorrelogram), texture(CWT moments) and shape(Hu invariant moments) features. As a color feature, a color autocorrelogram is chosen by extracting from the hue and saturation components of a color image(HSV). As a texture, shape and position feature are extracted from the value component. For efficient similarity confutation, the extracted features(color autocorrelogram, Hu invariant moments, and CWT moments) are combined and then precision and recall are measured. Experiment results for Corel and VisTex DBs show that the proposed image retrieval algorithm has 94.8% Precision, 90.7% recall and can successfully apply to image retrieval system.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.47-52
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• 2006

This paper proposes a method of content-based image retrieval using region feature vector in order to overcome disadvantages of existing color histogram methods. The color histogram methods have a weak point that reduces accuracy because of quantization error, and more. In order to solve this, we convert color information to HSV space and quantize hue factor being purecolor information and calculate histogram and then use thus for retrieval feature that is robust in brightness, movement, and rotation. Also we solve an insufficient part that is the most serious problem in color histogram methods by dividing an image into sixteen regions and then comparing each region. We improve accuracy by edge and DC of DCT transformation. As a result of experimenting with 1,000 color images, the proposed method has showed better precision than the existing methods.

• Food Science and Preservation
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• v.20 no.6
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• pp.760-765
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• 2013

The image analysis as a tool for evaluation of browning degree on fresh-cut lotus root was studied. The fresh-cut lotus root treated as 4 groups (Cont-without any treatment, DB-blanching at $50^{\circ}C$ for 5 min in distilled water, AB-blanching at $45^{\circ}C$ for 5 min in 1% ascorbic acid, CB-blanching at $45^{\circ}C$ for 5 min in 1% citric acid). The samples treated with each methods were packaged with 0.04 mm polyethylene bag ($25cm{\times}30cm$) and stored at $4^{\circ}C$ for 9 days. On the RGB color space, the AB and CB group showed high R, G, B value. On the HSV and CIE $L^*a^*b^*$ color space, the AB and CB group showed low browning area, $a^*$, $b^*$ value and high $L^*$ value. Polyphenol oxidase activity was low in the AB and CB groups in all storage period. This result means that the AB and CB groups were inhibited the development of tissue browning. The result of sensory evaluation also supported this opinion. And the correlation coefficient between sensory evaluation with all color values was over 0.84. Especially, the $L^*$ value showed the highest correlation coefficient (0.93). In conclusion, the image analysis is suitable for analysis of browning degree on fresh-cut lotus root by analyzing diverse color value.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.2
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• pp.103-108
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• 2012

Recently, as the prevalence of high-performance mobile devices and the application of the multimedia content are expanded, Super Resolution (SR) technique which reconstructs low resolution images to high resolution images is becoming important. And in the mobile devices, the development of the SR algorithm considering the operation quantity or memory is required because of using the restricted resources. In this paper, we propose a new single frame fast SR technique suitable for mobile devices. In order to prevent color distortion, we change RGB color domain to HSV color domain and process the brightness information V (Value) considering the characteristics of human visual perception. First, the low resolution image is enlarged by the improved fast back projection considering the noise elimination. And at the same time, the reliable edge map is extracted by using the LoG (Laplacian of Gaussian) filtering. Finally, the high definition picture is reconstructed by using the edge information and the improved back projection result. The proposed technique removes effectually the unnatural artefact which is generated during the super resolution restoration, and the edge information which can be lost is amended and emphasized. The experimental results indicate that the proposed algorithm provides better performance than conventional back projection and interpolation methods.