• 한국지형공간정보학회:학술대회논문집
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• 2002.11a
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• pp.117-122
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• 2002

Change detection is a useful technology that can be applied to various fields, taking temporal change information with the comparison and analysis among multi-temporal satellite images. Especially, change detection that utilizes high-resolution satellite imagery can be implemented to extract useful change information for many purposes, such as the environmental inspection, the circumstantial analysis of disaster damage, the inspection of illegal building, and the military use, which cannot be achieved by lower middle-resolution satellite imagery. However, because of the special characteristics that result from high-resolution satellite imagery, it cannot use a pixel-based method that is used for low-resolution satellite imagery. Therefore, it must be used a feature-based algorithm based on the geographical and morphological feature. This paper presents the system that builds the change map by digitizing the boundary of the changed object. In this system, we can make the change map using manual or semi-automatic digitizing through the user interface implemented with a floating window that enables to detect the sign of the change, such as the construction or dismantlement, more efficiently.

• The KIPS Transactions:PartD
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• v.15D no.6
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• pp.825-840
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• 2008

Refactoring is a kind of software modification process that improves system qualities internally but maintains system functions externally. What should be improved on the existing source codes should take precedence over the others in such a modification process using this refactoring. Martin Fowler and Kent Beck proposed a method that identifies code smells for this purpose. Also, some studies on determining what refactoring will be applied to which targets through detecting code smells in codes were presented. However, these studies have a lot of disadvantages that show a lack of precise description for such code smells and detect limited code smells only. In addition, these studies showed other disadvantages that generate ambiguity in behavior preservation due to the fact that a description method of pre-conditions for the behavior preservation is included in a refactoring process or unformalized. Thus, our study represents a precise specification of code smells using OCL and proposes a framework that performs a refactoring process through the automatic detection of code smells using an OCL interpreter. Furthermore, we perform the automatic detection in which the code smells are be specified by using OCL to the java program and verify its applicability and effectivity through applying a refactoring process.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.1
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• pp.30-38
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• 2003

This paper presents an efficient region-based motion segmentation method for segmenting of moving objects in a traffic scene with a focus on a Video Monitoring System (VMS). The presented method consists of two phases: motion detection and motion segmentation. Using the adaptive thresholding technique, the differences between two consecutive frames are analyzed to detect the movements of objects in a scene. To segment the detected regions into meaningful objects which have the similar intensity and motion information, the regions are initially segmented using a k-means clustering algorithm and then, the neighboring regions with the similar motion information are merged. Since we deal with not the whole image, but the detected regions in the segmentation phase, the computational cost is reduced dramatically. Experimental results demonstrate robustness in the occlusions among multiple moving objects and the change in environmental conditions as well.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.355-366
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• 2022

This paper proposes a microcode-based neural network accelerator controller for artificial intelligence accelerators that can be reconstructed using a programmable architecture and provide the advantages of low-power and ultra-small chip size. In order for the target accelerator to support various neural network models, the neural network model can be converted into microcode through microcode compiler and mounted on accelerator to control the operators of the accelerator such as datapath and memory access. While the proposed controller and accelerator can run various CNN models, in this paper, we tested them using the YOLOv2-Tiny CNN model. Using a system clock of 200 MHz, the Controller and accelerator achieved an inference time of 137.9 ms/image for VOC 2012 dataset to detect object, 99.5ms/image for mask detection dataset to detect wearing mask. When implementing an accelerator equipped with the proposed controller as a silicon chip, the gate count is 618,388, which corresponds to 65.5% reduction in chip area compared with an accelerator employing a CPU-based controller (RISC-V).

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.79-94
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• 2007

In the ubiquitous computing age which uses a high quantity network, mobile devices such as wearable and hand-held ones with a small tamers and a wireless communication module will be widely used in near future. Thus, a lot of researches about an augmented game on mobile devices have been attempted recently. The existing augmented games used a traditional 'backpack' system and a pattern marker. The 'backpack' system is expensive, cumbersome and inconvenient to use, and because of the pattern marker, it is only possible to play the game in the previously installed palace. In this paper, we propose an augmented game called Flying Cake using a face region to create the virtual object(character) without the pattern marker, which manually indicates an overlapped location of the virtual object in the real world, on a small and mobile PDA instead of the cumbersome hardware. Flying Cake is an augmented shooting game. This game supplies us with two types: 1) a single player which attacks a virtual character on images captured by a camera in an outdoor physical area, 2) dual players which attack the virtual character on images which we received through a wireless LAN. We overlap the virtual character on the face region using a face detection technique, and users play Flying Cake though attacking the virtual character. Flying Cake supplies new pleasure to flayers with a new game paradigm through an interaction between the user in the physical world captured by the PDA camera and the virtual character in a virtual world using the face detection.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.165-167
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• 2022

The proportion of cat cats among companion animals has been increasing at an average annual rate of 25.4% since 2012. Cats have strong wildness compared to dogs, so they have a characteristic of hiding diseases well. Therefore, when the guardian finds out that the cat has a disease, the disease may have already worsened. Symptoms such as anorexia (eating avoidance), vomiting, diarrhea, polydipsia, and polyuria in cats are some of the symptoms that appear in cat diseases such as diabetes, hyperthyroidism, renal failure, and panleukopenia. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia (drinking a lot of water), polyuria (a large amount of urine), and frequent urination (urinating frequently) more quickly. In this paper, 1) Efficient version of DeepLabCut for posture prediction running on an artificial intelligence server, 2) yolov4 for object detection, and 3) LSTM are used for behavior prediction. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the main server system.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.119-125
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• 2023

Through the Ukraine-Russia war, the military importance of drones is being reassessed, and North Korea has completed actual verification through a drone provocation towards South Korea at 2022. Furthermore, North Korea is actively integrating artificial intelligence (AI) technology into drones, highlighting the increasing threat posed by drones. In response, the Republic of Korea military has established Drone Operations Command(DOC) and implemented various drone defense systems. However, there is a concern that the efforts to enhance capabilities are disproportionately focused on striking systems, making it challenging to effectively counter swarm drone attacks. Particularly, Air Force bases located adjacent to urban areas face significant limitations in the use of traditional air defense weapons due to concerns about civilian casualties. Therefore, this study proposes a new passive air defense method that aims at disrupting the object detection capabilities of AI models to enhance the survivability of friendly aircraft against the threat posed by AI based swarm drones. Using laser-based adversarial examples, the study seeks to degrade the recognition accuracy of object recognition AI installed on enemy drones. Experimental results using synthetic images and precision-reduced models confirmed that the proposed method decreased the recognition accuracy of object recognition AI, which was initially approximately 95%, to around 0-15% after the application of the proposed method, thereby validating the effectiveness of the proposed method.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.83-93
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• 2013

Recently, the SURF algorithm, which is conjugated for object tracking system as part of many computer vision applications, is a well-known scale- and rotation-invariant feature detection algorithm. The SURF, due to its high computational complexity, there is essential to develop a hardware accelerator in order to be used on an IP in embedded environment. However, the SURF requires a huge local memory, causing many problems that increase the chip size and decrease the value of IP in ASIC and SoC system design. In this paper, we proposed a way to design a SURF algorithm in hardware with greatly reduced local memory by partitioning the algorithms into several Sub-IPs using external memory and a DMA. To justify validity of the proposed method, we developed an example of simplified object tracking algorithm. The execution speed of the hardware IP was about 31 frame/sec, the logic size was about 74Kgate in the 30nm technology with 81Kbytes local memory in the embedded system platform consisting of ARM Cortex-M0 processor, AMBA bus(AHB-lite and APB), DMA and a SDRAM controller. Hence, it can be used to the hardware IP of SoC Chip. If the image processing algorithm akin to SURF is applied to the method proposed in this paper, it is expected that it can implement an efficient hardware design for target application.

• Convergence Security Journal
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• v.24 no.1
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• pp.59-68
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• 2024

With advancements in artificial intelligence technology, intelligent CCTV systems are being deployed across various environments, such as river bridges and construction sites. However, a conflict arises regarding the opening and closing of rooftop access points due to concerns over potential accidents and crime incidents and their role as emergency evacuation spaces. While the relevant law typically mandates the constant opening of designated rooftop access points, closures are often tacitly permitted in practice for security reasons, with a lack of appropriate legal measures. In this context, this study proposes a detection system utilizing intelligent CCTV to respond to emergencies that may occur on rooftops. We develop a system based on the YOLOv5 object detection model to detect assault and suicide attempts by jumping, introducing a new metric to assess them. Experimental results demonstrate that the proposed system rapidly detects assault and suicide attempts with high accuracy. Additionally, through a legal analysis of rooftop access point management, deficiencies in the legal framework regarding rooftop access and CCTV installation are identified, and improvement measures are proposed. With technological and legal improvements, we believe that crime and accident incidents in rooftop environments will decrease.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.704-709
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• 2003

The digital image can be distorted by a noise for a transmission or other elements of system. It happen to be vague of a boundary side in the division of an image object, especially, boundary side of an input image is very important because it can be determined to the division and detection element in pattern recognition. Therefore it is proposed an edge detection method of optimal to divide and detect exactly a boundary part. In this paper, it detected the optimal edge with applying this image to Meyer wavelet-CNN algorithm, after it does level up a boundary side of an image by using the adaptive morphology as the threshold of an input image. It confirmed that the proposed algorithm is more superior to the conventional methods and the conventional Sobel method which is an image edge detection algorithm. Especially, it is confirmed by simulation that the proposed algorithm can be got the better result edge at the place of closing to each edges and having smoothly curved line.