• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.103-109
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• 2018

Purpose: This study has been conducted to develop a potato yield monitoring system, consisting of a segmentation algorithm to detect potatoes scattered on a soil surface and a counting system to count the number of potatoes and convert the data from two-dimensional images to masses. Methods: First, a segmentation algorithm was developed using top-hat filtering and processing a series of images, and its performance was evaluated in a stationary condition. Second, a counting system was developed to count the number of potatoes in a moving condition and calculate the mass of each using a mass estimation equation, where the volume of a potato was obtained from its two-dimensional image, and the potato density and a correction factor were obtained experimentally. Experiments were conducted to segment potatoes on a soil surface for different potato sizes. The counting system was tested 10 times for 20 randomly selected potatoes in a simulated field condition. Furthermore, the estimated total mass of the potatoes was compared with their actual mass. Results: For a $640{\times}480$ image size, it took 0.04 s for the segmentation algorithm to process one frame. The root mean squared deviation (RMSD) and average percentage error for the measured mass of potatoes using this counting system were 12.65 g and 7.13%, respectively, when the camera was stationary. The system performance while moving was the best in L1 (0.313 m/s), where the RMSD and percentage error were 6.92 g and 7.79%, respectively. For 20 newly prepared potatoes and 10 replication measurements, the counting system exhibited a percentage error in the mass estimation ranging from 10.17-13.24%. Conclusions: At a travel speed of 0.313 m/s, the average percentage error and standard deviation of the mass measurement using the counting system were 12.03% and 1.04%, respectively.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.17-24
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• 2012

Andre Bazin called the movie frame as "the window open to the world." This expression is close to realization through 3D films. The 'Avatar' released in 2009 was a new turning point for 3D films. Nowadays the theory and information about 3D films is overflowed. It is necessary to find practices and to accumulate data useful in production of 3D films. There are several ways of working to achieve high quality 3D films. In any way that's chosen, there are priorities to be considered to create well-balanced 3D films. The aim of this article is to review primary considerations in film-making and share the technical issues experienced during the production of "Let's go to the amusement park again, Mom." Because the current practical knowledge in making 3D film is shallow, this article will offer a possible reference for further research.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1243-1253
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• 1993

Visual features of a mushroom(Lentinus Edodes L) are critical in sorting and grading as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. Though actions involved in human grading looks simple, a decision making undereath the simple action comes form the results of the complex neural processing of the visual image. And processing details involved in the visual recognition of the human brain has not been fully investigated yet. Recently, however, an artificial neural network has drawn a great attention because of its functional capability as a partial substitute of the human brain. Since most agricultural products are not uniquely defined in its physical properties and do not have a well defined job structure, a research of the neuro-net based human like information processing toward the agricultural product and processing are widely open and promising. In this pape , neuro-net based grading and sorting system was developed for a mushroom . A computer vision system was utilized for extracting and quantifying the qualitative visual features of sampled mushrooms. The extracted visual features and their corresponding grades were used as input/output pairs for training the neural network and the trained results of the network were presented . The computer vision system used is composed of the IBM PC compatible 386DX, ITEX PFG frame grabber, B/W CCD camera , VGA color graphic monitor , and image output RGB monitor.

• Journal of Biosystems Engineering
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• v.26 no.6
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• pp.571-578
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• 2001

Production of green pepper has increased for ten years in Korea, as customer's preference of a pepper tuned to fiesta one. This study was conducted to develop an on-line fading algorithm of green pepper using machine vision and aimed to develop the automatic on-line grading and sorting system. The machine vision system was composed of a professive scan R7B CCD camera, a frame grabber and sets of 3-wave fluorescent lamps. The length and curvature, which were main quality factors of a green pepper were measured while removing the stem region. The first derivative of the thickness profile was used to remove the stem area of the segmented image of the pepper. A new boundary was generated after the stem was removed and a baseline of a pepper which was used for the curvature determination was also generated. The developed algorithm showed that the accuracy of the size measurement was 86.6% and the accuracy of the bent was 91.9%. Processing time spent far grading was around 0.17 sec per pepper.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5854-5860
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• 2014

The on-site performance of a vision-based displacement measurement system (VDMS) was evaluated through a field test on a bridge. The VDMS used in this study is composed of a camera, a marker, a frame grabber, and a laptop. The system measures the displacement by attaching a marker at the location to be measured on the structure, by capturing images of that marker with a fixed rate, and by processing a series of images using a planar homography technique. The developed system was first validated from a laboratory test using a small-scale building structure. The VDMS was then employed in a field test on a railroad bridge with a KTX train running under various conditions. The on-site performance was evaluated by comparing the obtained displacement using the VDMS with the displacement measured from a laser Doppler vibrometer (LDV), which is an expensive and accurate displacement measurement device.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2335-2340
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• 2009

This paper presents how to implement Markerless Augmented Reality and how to create and apply reference data sets. There are three parts related with implementation: setting camera, creation of reference data set, and tracking. To create effective reference data sets, we need a 3D model such as CAD model. It is also required to create reference data sets from various viewpoints. We extract the feature points from the mode1 image and then extract 3D positions corresponding to the feature points using ray tracking. These 2D/3D correspondence point sets constitute a reference data set of the model. Reference data sets are constructed for various viewpoints of the model. Fast tracking can be done using a reference data set the most frequently matched with feature points of the present frame and model data near the reference data set.

• Korean Journal of Applied Biomechanics
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• v.16 no.3
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• pp.165-172
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• 2006

The purpose of this study was to determine effects of 12-week wearing of unstable shoe on the standing posture and gait mechanics. Nine healthy men were asked to wear the unstable shoes for 12-week and walk for 30 minute everyday. Their standing posture and gait mechanics were measured before and after treatment. Standing posture was measured for each side(anterior, posterior, lateral) for standing position. And gait analysis was measured joint angle of a right lower limb between first right heel contact and second right heel contact. Kinematic data were collected using video camera at 30 frame per seconds. Statistical analysis was paired t-test(p<.05) to compare before training with after that. A head tilt angle was significantly decreased for posterior side(p<.05). The angle of between center of line and surface was significantly decreased at midstance and take off during walking(p<.05). Ankle dorsiflexion significantly increased at heel contact2(p<.05) and ankle plantarflexion significantly increased at midstance and midswing(p<.05). The increase of ankle dorsiflexion showed that our results consisted with previous study. In conclusion, there was not large significant difference in static standing posture but joint angle of lower limb represented many changes with increasing of ankle motion during walking. These were of benefit to body by increasing leg muscle activity but it was necessary for man having a ankle problem to consider. Further studies concerning optimum outsole angle of unstable shoes are necessary.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.45-51
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• 2006

Recently, the IDS(Intrusion Detection System) using a video camera is an important part of the home security systems which start gaining popularity. However, the video intruder detection has not been widely used in the home surveillance systems due to its unreliable performance in the environment with abrupt illumination change. In this paper, we propose an effective moving edge extraction algerian from a sequence image. The proposed algorithm extracts edge segments from current image and eliminates the background edge segments by matching them with reference edge list, which is updated at every frame, to find the moving edge segments. The test results show that it can detect the contour of moving object in the noisy environment with abrupt illumination change.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1577-1585
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• 1999

In this paper, we propose detection methods for gradual scene changes such as dissolve, pan, and zoom. The proposal method to detect a dissolve region uses scene features based on spatial statistics of the image. The spatial statistics to define shot boundaries are derived from squared means within each local area. We also propose a method of the camera motion detection using four representative motion vectors in the background. Representative motion vectors are derived from macroblock motion vectors which are directly extracted from MPEG streams. To reduce the implementation time, we use DC sequences rather than fully decoded MPEG video. In addition, to detect the gradual scene change region precisely, we use all types of the MPEG frames(I, P, B frame). Simulation results show that the proposed detection methods perform better than existing methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.95-104
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• 2012

Pattern recognition using ensemble classifiers is composed of strong classifier which consists of many weak classifiers. In this paper, we used feature extraction to organize strong classifier using static camera sequence. The strong classifier is made of weak classifiers which considers environmental factors. So the strong classifier overcomes environmental effect. Proposed method uses binary foreground image by frame difference method and the boosting is used to train crowdedness model and recognize crowdedness using features. Combination of weak classifiers makes strong ensemble classifier. The classifier could make use of potential features from the environment such as shadow and reflection. We tested the proposed system with road sequence and subway platform sequence which are included in "AVSS 2007" sequence. The result shows good accuracy and efficiency on complex environment.