• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3784-3789
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• 2021

We report a simple technique for direct neutron spectroscopy using pure LaCl₃ crystals. Pure LaCl₃ crystals exhibit considerably better pulse shape discrimination (PSD) capabilities with relatively good energy resolution as compared with Ce-doped LaCl₃ crystals. Single crystals of pure and Ce-doped LaCl₃ were grown using an inhouse-developed Bridgman furnace. PSD capabilities of these crystals were investigated using ²⁴¹Am and ¹³⁷Cs sources. Fast neutron detection was tested using a²⁵²Cf source and three separate bands corresponding to electron, proton, and alpha were observed. The proton band induced by the ³⁵Cl(n,p)³⁵S reaction can be used for direct neutron spectroscopy because proton energy is proportional to incident neutron energy. Owing to good scintillation performance and excellent PSD capabilities, pure LaCl₃ is a promising candidate for space detectors and other applications that necessitate gamma/fast neutron discrimination capability.

• Journal of Korea Multimedia Society
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• v.12 no.6
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• pp.794-803
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• 2009

In this paper, we will present a container auto-landing system, the system use the stereo camera to measure the container depth information. And the container region can be detected by using its hough line feature. In the line feature detection algorithm, we will detect the parallel lines and perpendicular lines which compose the rectangle region. Among all the candidate regions, we can select the region with the same aspect-ratio to the container. The region will be the detected container region. After having the object on both left and right images, we can estimate the distance from camera to object and container dimension. Then all the detect dimension information and depth inform will be applied to reconstruct the virtual environment of crane which will be introduce in this paper. Through the simulation result, we can know that, the container detection rate achieve to 97% with simple background. And the estimation algorithm can get a more accuracy result with a far distance than the near distance.

• Journal of information and communication convergence engineering
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• v.12 no.3
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• pp.193-197
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• 2014

Edges are a robust feature for object detection. In this paper, we present an edge-based background modeling method for the detection of moving objects. The edges in the image frames were mapped using robust Canny edge detector. Two edge maps were created and combined to calculate the ultimate moving-edge map. By selecting all the edge pixels of the current frame above the defined threshold of the ultimate moving edges, a temporary background-edge map was created. If the frequencies of the temporary background edge pixels for several frames were above the threshold, then those edge pixels were treated as background edge pixels. We conducted a performance comparison with previous works. The existing edge-based moving-object detection algorithms pose some difficulty due to the changes in background motion, object shape, illumination variation, and noises. The result of the performance evaluation shows that the proposed algorithm can detect moving objects efficiently in real-world scenarios.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.459-466
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• 2006

The objective of this study is to improve the accuracy of damage detection using natural frequency and modal strain energy. The following approaches are used to achieve the goal. First, modal strain energy is introduced and newly GA-based damage detection technique using natural frequency and modal strain energy is proposed. Next, to verify efficiency of the proposed technique, damage scenarios for free-free beams are designed and the vibration modal tests as damage cases are conducted. Finally, feasibility of proposed technique is verified in comparison with a GA-based damage detection technique using natural frequency and mode shape.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.85-88
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• 2009

In this paper, we propose a DRF-based object detection method using the object adaptive patch in the satellite imagery. It is a Discriminative Random Fields (DRF) based work, so the detection is done by labeling to the possible patches in the image. For the feature information of each patch, we use the multi-scale and object adaptive patch and its texton histogram, instead of using the single scale and fixed grid patch. So, we can include contextual layout of texture information around the object. To make object adaptive patch, we use "superpixel lattice" scheme. As a result, each group of labeled patches represents the object or object's presence region. In the experiment, we compare the detection result with a fixed grid scheme and shows our result is more close to the object shape.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4489-4501
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• 2014

We propose a novel lane detection method based on classification in image sequences. Both structural and statistical features of the extracted bright shape are applied to the neural network for finding correct lane marks. The features used in this paper are shown to have strong discriminating power to locate correct traffic lanes. The traffic lanes detected in the current frame is also used to estimate the traffic lane if the lane detection fails in the next frame. The proposed method is fast enough to apply for real-time systems; the average processing time is less than 2msec. Also the scheme of the local illumination compensation allows robust lane detection at nighttime. Therefore, this method can be widely used in intelligence transportation systems such as driver assistance, lane change assistance, lane departure warning and autonomous vehicles.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.458-460
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• 2003

This paper proposes new algorithms for cloudy area detection by GHA (Generalized Hebbian Algorithm) and SOFM (Self-Organized Feature Map). SOFM and GHA are unsupervised neural networks and are used for pattern classification and shape detection of satellite image. Proposed algorithm is based on block based image processing that size is 16${\times}$16. Results of proposed algorithm shows good performance of cloudy area detection except blur cloudy area.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.524-534
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• 2022

In this paper, we produce Trash Object Detection (TOD) dataset to solve trash detection problems. A well-organized dataset of sufficient size is essential to train object detection models and apply them to specific tasks. However, existing trash datasets have only a few hundred images, which are not sufficient to train deep neural networks. Most datasets are classification datasets that simply classify categories without location information. In addition, existing datasets differ from the actual guidelines for separating and discharging recyclables because the category definition is primarily the shape of the object. To address these issues, we build and experiment with trash datasets larger than conventional trash datasets and have more than twice the resolution. It was intended for general household goods. And annotated based on guidelines for separating and discharging recyclables from the Ministry of Environment. Our dataset has 10 categories, and around 33K objects were annotated for around 5K images with 1280×720 resolution. The dataset, as well as the pre-trained models, have been released at https://github.com/jms0923/tod.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.525-532
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• 2000

A new spectroscopic method for pesticide residues detection on agricultural products was developed. The general determination methods are high performance liquid chromatography (HPLC), gas chromatography (GC) or GC-mass spectrometry. They have provided relatively good detection limit and accuracy with complicated and time-consuming (5hrs above) procedures. In addition freshness is very important for evaluating qualities of agricultural products. This requires a simple and fast method for detection of pesticides. Reflectance, transmittance and fluorescence spectrometry of pesticides were tested using UV range because most of pesticides contain conjugation band in the molecular structures. Fluorescence spectrometry showed better sensitive to detect pesticide residues than did reflectance and transmittance spectrometry. Intensity and shape of fluorescence spectra showed different patterns with different structures of pesticides. Detection limit for fluorescence spectrometry was 0.1 ppm to 10 ppm depending on the structures of pesticides. Application of fluorescence spectrometry appears to be an easy method for detection of pesticide residues on agricultural products.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.304-309
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• 2015

On construction sites, it is important to monitor the performance of construction equipment and workers to achieve successful construction project management; especially, vision-based detection methods have advantages for the real-time site data collection for safety and productivity analyses. Although many researchers developed vision-based detection methods with acceptable performance, there are still limitations to be addressed: 1) sensitiveness to the shape and appearance changes of moving objects in difference working postures, and 2) high computation time. To deal with the limitations, this paper proposes a detection algorithm of construction equipment based on Integral Channel Features. For validation, 16,850 frames of video streams were recorded and analyzed. The results showed that the proposed method worked in high performance in terms of accuracy and processing time. In conclusion, the developed method can help to understand useful site information including working pattern, working time and input manpower analyses.