• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.161-166
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• 2021

The term parking management system usually refers to the custom built hardware intensive systems installed in building and malls. However, there are many places where such expensive solutions cannot be installed due to various reasons, like cost and urgent/temporary setup requirements. This project focuses on developing a parking management system based on image processing to detect vacant parking slot in an area where automated systems are not installed. Camera images of the parking area are subjected to image processing algorithm which marks virtual slots in the area and extracts occupancy information to guide the incoming drivers about availability and position of vacant spaces. The application consists of two interfaces: one for the guidance of the incoming drivers and the other one for the administrator. The later interface also informs the administrator if a car is not parked properly in the virtual slot. This parking system would reduce the stress and time wastage associated with car parking and would make the management of such areas less costly.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.293-302
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• 2023

This study examines and proposes standardization approaches to address the heterogeneous issues of metadata in drone imagery within the agricultural sector. Image metadata comes in various formats depending on different camera manufacturers, with most utilizing EXIF and XMP. The metadata of cameras used in fixed-wing and rotary-wing platforms, along with the metadata requirements in image alignment software, were analyzed for sensors like DJI XT2, MicaSense RedEdge-M, and Sentera Double4K. In the agricultural domain, multispectral imagery is crucial for vegetation analysis, making the provision of such imagery essential. Based on Pix4D SW, a comparative analysis of metadata attributes was performed, and necessary elements were compiled and presented as a proposed standardization (draft) in the form of tag information.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.919-926
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• 2023

In this paper, we implemented the surveillance camera system capable of day and night shooting. To this end, it is designed to capture clear images even at night using a CMOS image sensor as well as an IR-LED. In addition, a relatively simple motion detection algorithm was proposed through color model separation. Motions can be detected by extracting only the H channel from the color model, dividing the image into blocks, and then applying the block matching method using the average color value between consecutive frames. When motions are detected during filming, an alarm sounds automatically and a day and night motion detection system is implemented that can capture and save the event screen to a PC.

• Journal of Sensor Science and Technology
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• v.33 no.3
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• pp.179-184
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• 2024

In the car industry, welding is a fundamental linking technique used for joining components, such as steel, molds, and automobile parts. However, accurate inspection is required to test the reliability of the welding components. In this study, we investigate the detection of weld beads using 2D image processing in an automatic recognition system. The sample image is obtained using a 2D vision camera embedded in a lighting system, from where a portion of the bead is successfully extracted after image processing. In this process, the soot removal algorithm plays an important role in accurate weld bead detection, and adopts adaptive local gamma correction and gray color coordinates. Using this automatic recognition system, geometric parameters of the weld bead, such as its length, width, angle, and defect size can also be defined. Finally, on comparing the obtained data with the industrial standards, we can determine whether the weld bead is at an acceptable level or not.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.159-166
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• 2008

Video image processing systems (VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on a wide-area detection algorithm provide traffic parameters such as flow and velocity as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. However, unlike human vision, VIPS cameras have difficulty in recognizing vehicle movements over a detection zone longer than 100 meters. Over such a distance, the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera is limited to detection zones under 100m. This paper develops a methodology capable of monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long distance tracking algorithm for use over 200m is developed with multi-closed circuit television (CCTV) cameras. The algorithm is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of incident detection.

• Journal of Bio-Environment Control
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• v.24 no.3
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• pp.210-216
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• 2015

Purpose of this study was a development of an image processing algorithm to recognize paprika and acquire it's 3D coordinates from stereo images to precisely control an end-effector of a paprika auto harvester. First, H and S threshold was set using HSI histogram analyze for extracting ROI(region of interest) from raw paprika cultivation images. Next, fundamental matrix of a stereo camera system was calculated to process matching between extracted ROI of corresponding images. Epipolar lines were acquired using F matrix, and $11{\times}11$ mask was used to compare pixels on the line. Distance between extracted corresponding points were calibrated using 3D coordinates of a calibration board. Non linear regression analyze was used to prove relation between each pixel disparity of corresponding points and depth(Z). Finally, the program could calculate horizontal(X), vertical(Y) directional coordinates using stereo camera's geometry. Horizontal directional coordinate's average error was 5.3mm, vertical was 18.8mm, depth was 5.4mm. Most of the error was occurred at 400~450mm of depth and distorted regions of image.

• Journal of Korea Multimedia Society
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• v.14 no.9
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• pp.1125-1137
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• 2011

Recently, there have been previous research about the iris recognition in mobile device to increase portability, whose accuracy is affected by the quality of iris image. Iris image is affected by illumination environment during the image acquisition. The existing system has high accuracy in indoor environment. However the accuracy is degraded in outdoor environment, because the gray levels of iris patterns in image are changed, and ghost and eyelash shading regions are produced by the sunlight of various wavelengths into iris region. To overcome these problems, we propose new mobile iris camera system which uses the near-infrared (NIR) light illuminator of 850 nm and band pass filter (BPF) of 850 nm. To measure the performance of the proposed system, we compared it to the existing one with the iris images captured in indoor and outdoor sunlight environments in terms of the equal error rates (EER) based on false acceptance rate (FAR) and false rejection rate (FRR). The experimental result showed that the proposed system had the lower EERs than those of previous system by 0.96% (with frontal light in indoors), 4.94% (with frontal light in outdoor), 9.24% (with side light in outdoor), and 7% (with back light in outdoor), respectively.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.315-320
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• 2017

Estimating the correct pose of augmented objects on the real camera view efficiently is one of the most important questions in image tracking area. In computer vision, Homography is used for camera pose estimation in augmented reality system with markerless. To estimating Homography, several algorithm like SURF features which extracted from images are used. Based on extracted features, Homography is estimated. For this purpose, RANSAC algorithm is well used to estimate homography and DCS-RANSAC algorithm is researched which apply constraints dynamically based on Constraint Satisfaction Problem to improve performance. In DCS-RANSAC, however, the dataset is based on pattern of feature distribution of images manually, so this algorithm cannot classify the input image, pattern of feature distribution is not recognized in DCS-RANSAC algorithm, which lead to reduce it's performance. To improve this problem, we suggest the KCS-RANSAC algorithm using K-means clustering in CS-RANSAC to cluster the images automatically based on pattern of feature distribution and apply constraints to each image groups. The suggested algorithm cluster the images automatically and apply the constraints to each clustered image groups. The experiment result shows that our KCS-RANSAC algorithm outperformed the DCS-RANSAC algorithm in terms of speed, accuracy, and inlier rate.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.178-185
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• 2011

The recent development of 3D and its application contents have made it possible for people to experience more various 3D contents such as 3D/4D, VR, 3D ride film, I-max, sensory 3D games at theme parks, large-scale exhibitions, 4D cinemas and Video ride. Among them, Video ride, a motion-based genre, especially is getting more popularity, where viewers are immersed in and get indirect experiences in virtual reality. In this study, the production process of the genre of sensory 3D image getting attention recently and ride film are introduced. In the material selection of 3D images, the space and the setting up which is suitable to the fierce movement of rides are studied and some examples of the realization of creative direction ideas and effective technologies using the functions of Stereo Camera which has been first applied to MAYA 2009 are also illustrated. When experts in this 3D image production create more interesting stories with the cultural diversity and introduce enhanced 3D production techniques for excellent contents, domestic relevant companies will be sufficiently able to compete with their foreign counterparts and further establish their successfully unique and strong domains in the image contents sector.