• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.166-175
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• 2020

Recently, application fields for processing and using digital image contents in various forms and types are rapidly increasing. Since image content is high value-added content, the intellectual property rights of this content must be protected in order to activate the production and use of the digital image content. In this paper, we propose a deep learning based watermark embedding and extraction network. The proposed method is to maximize the robustness of the watermark against malicious/non-malicious attacks while preserving the invisibility of the host image. This network consists of a preprocessing network that changes the watermark to have the same resolution as the host image, a watermark embedding network that embeds watermark data while maintaining the resolution of the host image by three-dimensionally concatenating the changed host image and the watermark information, and a watermark extraction network that reduces the resolution and extracts watermarks. This network verifies the invisibility and robustness of the proposed method by experimenting with various pixel value change attacks and geometric attacks against various watermark data and host images with various resolutions, and shows that this method is universal and practical.

• The KIPS Transactions:PartA
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• v.16A no.3
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• pp.209-216
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• 2009

The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2: image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.465-473
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• 2002

Images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in radiography is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in reading. We have proposed adaptive weighted median(AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by homogeneous factor(HF). Homogeneous factor(HF) from the quantum noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the detection systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by visual C++ language on a IBM-PC Pentium 550 for testing purposes, the effects and results of the noise filtering were proposed by comparing with images of the other existing filtering methods.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.3
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• pp.44-51
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• 2009

It is very important to verify generated setup errors in cancer therapy by using a high energy radiation and to perform the precise radiation therapy. Specially, the verification of treatment position is very crucial in special therapies like fractionated stereotatic radiotherapy (FSRT). The FSRT uses normally high-dose, small field size for treating small intracranial lesions. To estimate the developed FSRT system, the isocenter accuracy of gantry, couch and collimator were performed and a total of inaccuracy was less than ${\pm}1mm$. Precise beam targeting is crucial when using high-dose, small field size FSRT for treating small intracranial lesions. The EPID image of the 3mm lead ball mounted on the isocenter with a 25mm collimator cone was acquired and detected to the extent of one pixel (0.76mm) after comparing the difference between the center of a 25mm collimator cone and a 3 mm ball after processing the EPID image. In this paper, the radiation treatment efficiency can be improved by performing precise radiation therapy with a developed video based EPID and FSRT at near real time

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.4
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• pp.103-109
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• 2007

Ortho images and Digital Elevation Model (DEM) have been applied in various fields. It is necessary to acquire Ground Control Points (GCPs) for processing high resolution satellite images. However surveying GCPs require many time and expense. This study was performed to investigate whether GCPs automatically extracted from ortho images and DTED Level 2 can be applied to sensor modeling for high resolution satellite images. We analyzed the performance of the sensor model established by GCPs extracted automatically. We acquired GCPs by matching satellite image against ortho images. We included the height acquired from DTED Level 2 data in these GCPs. The spatial resolution of the DTED Level 2 data is about 30m. Absolution accuracy of this data is below 18m above MSL. The spatial resolution of ortho image is 1m. We established sensor model from IKONOS images using GCPs extracted automatically and generated DEMs from the images. The accuracy of sensor modeling is about $4{\sim}5$ pixel. We also established sensor models using GCPs acquired based on GPS surveying and generated DEMs. Two DEMs were similar. The RMSE of height from the DEM by automatic GCPs and DTED Level 2 is about 9 m. So we think that GCPs by DTED Level 2 and ortho image can use for IKONOS sensor modeling.

• Journal of Korea Multimedia Society
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• v.8 no.9
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• pp.1258-1268
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• 2005

While the concept of Home Network is laying by and its interests are increasing by means of digitalizing of the information communication infrastructure, many efforts are in progress toward convenient lives. Moreover, as information household appliances which have a junction of connecting to the network are appearing over the past a few years, the demands against intellectual Home Services are increasing. In this paper, by being based upon Multimedia which is an essential factor for developing of various application services on ubiquitous computing environments, we suggest a simplified application model that could apply the information to the automated processing system after studying user's behavior patterns using authentication and access control for identity certification of users. In addition, we compared captured video images in the fixed range by pixel unit through some time and checked disorder of them. And that made safe of user certification as adopting self-developed certification method which was used 'Hash' algorism through salt function of 12 byte. In order to show the usefulness of this proposed model, we did some testing by emulator for control of information after construction for Intellectual Multimedia Server, which ubiquitous network is available on as a scheme so as to check out developed applications. According to experimental results, it is very reasonable to believe that we could extend various multimedia applications in our daily lives.

• Korean Journal of Digital Imaging in Medicine
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• v.11 no.2
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• pp.115-119
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• 2009

I think this will be valuable reference for assuring consistency and homogeneity of clarity and managing dental radiation equipment by experimentation of dental radiation equipment permanent which based on KS C IEC 61223-3-4 standard and KS C IEC 61223-2-7. Put a dental radiation generator and experiment equipment as source and film(sensor) length within 30 em, place the step-wedge above the film(sensor). Tie up tube voltage 60 kVp, tube current 7 mA and then get an each image through CCD sensor and film by changing the exposure time as 0.12sec, 0.25sec, 0.4sec. Repeat the test 5times as a same method. Measure the concentration of each stage of film image, which gained by experiment, using photometer. And the image that gained by CCD sensor, analyze the pixel value's change by using image J, which is analyzing image program provided by NIH(National Institutes of Health). In case of film, while 0.12sec and 0.25sec show regular rising pattern of density gap as exposure time's increase, 0.4sec shows low rather than 0.12sec and 0.25sec. In case of CCD sensor density test, the result shows opposite pattern of film. This makes me think that pixels of CCD's sensor can have 0~255 value but it becomes saturation if the value is over 255. The way that getting clear reception during decreasing human's exposed radiation is one of maintaining an equipment as a best condition. So we should keeping a dental radiation equipment's condition steadily through cyclic permanent test after factor examination. Even digital equipment doesn't maintain a permanent, it can maintain a clarity by post processing of image so that hard to set it as standard of permanent test. Therefore it would be more increase the accuracy that compare a film as standard image. Thus I consider it will be an important measurement to care for dental radiation equipment and warrant homogeneity, consistency of dental image's clarity through comparing pattern which is the result from factor test against cyclic permanent test.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.7C
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• pp.421-427
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• 2011

The importance of the real-time object recognition and tracking field has been growing steadily due to rapid advancement in the computer vision applications industry. As is well known, the mean-shift algorithm is widely used in robust real-time object tracking systems. Since the mentioned algorithm is easy to implement and efficient in object tracking computation, many say it is suitable to be applied to real-time object tracking systems. However, one of the major drawbacks of this algorithm is that it always converges to a local mode, failing to perform well in a cluttered environment. In this paper, an Optical Flow-based algorithm which fits for real-time recognition of multiple moving objects is proposed. Also in the tests, the newly proposed method contributed to raising the similarity of multiple moving objects, the similarity was as high as 0.96, up 13.4% over that of the mean-shift algorithm. Meanwhile, the level of pixel errors from using the new method keenly decreased by more than 50% over that from applying the mean-shift algorithm. If the data processing speed in the video surveillance systems can be reduced further, owing to improved algorithms for faster moving object recognition and tracking functions, we will be able to expect much more efficient intelligent systems in this industrial arena.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.361-368
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• 2014

The LPR(License plate recognition) system has been developed to efficient control for complex traffic environment and currently be used in many places. However, because of light, noise, background changes, environmental changes, damaged plate, it only works limited environment, so it is difficult to use in real-time. This paper presents a heuristic segmentation algorithm for robust to noise and illumination changes and introduce a real-time license plate recognition system using it. In first step, We detect the plate utilized Haar-like feature and Adaboost. This method is possible to rapid detection used integral image and cascade structure. Second step, we determine the type of license plate with adaptive histogram equalization, bilateral filtering for denoise and segment accurate character based on adaptive threshold, pixel projection and associated with the prior knowledge. The last step is character recognition that used histogram of oriented gradients (HOG) and multi-layer perceptron(MLP) for number recognition and support vector machine(SVM) for number and Korean character classifier respectively. The experimental results show license plate detection rate of 94.29%, license plate false alarm rate of 2.94%. In character segmentation method, character hit rate is 97.23% and character false alarm rate is 1.37%. And in character recognition, the average character recognition rate is 98.38%. Total average running time in our proposed method is 140ms. It is possible to be real-time system with efficiency and robustness.

• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.99-111
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• 2009

The result of Image segmentation, an indispensable process in image processing, significantly affects the analysis of an image. Despite the significance of image segmentation, it produces some problems when the variation of pixel values is large, or the boundary between background and an object is not clear. Also, these problems occur frequently when many objects in an image are placed very close by. In this paper, when the shape of objects in an image is circular, we proposed an algorithm which segment an each object in an image using the geometric characteristic of circular shape. The proposed algorithm is composed of 4 steps. First is the boundary edge extraction of whole object. Second step is to find the candidate points for further segmentation using the boundary edge in the first step. Calculating the representative circles using the candidate points is the third step. Final step is to draw the line connecting the overlapped points produced by the several erosions and dilations of the representative circles. To verify the efficiency of the proposed algorithm, the algorithm is compared with the three well-known cell segmentation algorithms. Comparison is conducted by the number of segmented region and the correctness of the inner segment line. As the result, the proposed algorithm is better than the well-known algorithms in both the number of segmented region and the correctness of the inner segment line by 16.7% and 21.8%, respectively.