• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.657-662
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• 2014

Usually, spatial information can be incorporated into histograms by taking histograms of a multiresolution image. For these reasons, many researchers are interested in multiresolution histogram processing. If the relation and sensitivity of the multiresolution images are well combined without loss of information, we can obtain satisfactory results in several fields of image processing including histogram equalization, specification and pattern matching. In this paper, we propose a multiresolution histogram specification method that improves the accuracy of histogram specification. The multiresolution decomposition technique is used in order to overcome the unique feature of a histogram specification affected by a quantization error of a digitalized image. The histogram specification is processed after the reduction of image resolution in order to enhance the accuracy of the results by histogram specification methods. The experimental results show that the proposed method enhances the accuracy of specification compared to conventional methods.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.418-422
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• 2005

In this paper, a novel algorithm capable of detecting generic obstacles on a flat surface is proposed. The algorithm fundamentally exploits a distortion phenomena taken place in remapping process of original stereo images to a virtual top-view. Based on the distortion phenomena, we construct stereo polar histograms of edge maps, detect peaks on them, and search for matched peaks on both histograms using a Dynamic Programming (DP). Eventually, the searched corresponding peaks lead to estimate obstacles' positions. The advantages of the proposed algorithm are that it is not largely affected by an intensity difference between a pair of stereo images and does not depend on the typical stereo matching methodologies. Furthermore, the algorithm identifies the obstacles' positions quite robustly.

• Korean Journal of Remote Sensing
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• v.11 no.1
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• pp.31-45
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• 1995

The values of brightness temperature difference (BTD) between 11um and 12um infrared channels may reflect amounts of low-level water vapor and cloud types due to the different absorptivity for water vapor between two channels. A simple method of classifying cloud types at night was proposed. Two-dimensional histograms of brightness temperature of the 11um channel and the BTD between the split window data over subareas around characteristic clouds such as Cb(cumulonimbus), Ci(cirrus), and Sc(stratocumulus) was constructed. Cb, Ci and Sc can be classified by seleting appropriate thresholds in the two-dimensional histograms. And we can see amounts of low-level water vapor in clear area as well as cloud types in cloudy area in the BTD image. The map of cloud types and low-level water vapor generated by this method was compared with 850hPa and 1000hPa relative humidity(%) of numerical analysis data and nephanalysis chart. The comparisons showed reasonable agreement.

• Nuclear Engineering and Technology
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• v.8 no.4
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• pp.219-229
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• 1976

A statistical approach is employed to investigate the relative advantages of several alternative fuel cycles suitable for a hypothetical 1125 MWe plant in Korea. All the fuel cost parameters are treated as statistical variables, each being associated with an appropriate probability distribution function. Through a random sampling procedure, the probability histograms on both capital requirements and break-even costs of various fuel cycle components are obtained. The histograms are then utilized to quantify the cost-benefit of the fuel cycle with reprocessing or the plutonium recycle over the throwaway cycle.

• Current Optics and Photonics
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• v.5 no.3
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• pp.278-288
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• 2021

We propose a characterization method for the scattering property of microspheres using spectroscopic optical coherence tomography (OCT). To prove the effectiveness of the proposed method, we prepare solutions of different concentrations using microspheres ranging from 28 to 2300 nm in diameter. Time-frequency analysis is performed on the measured interference spectrum of each solution, and the resulting spectroscopic information is converted into histograms for centroid wavelengths. The histograms present a very sensitive response to changes in the concentration and size of microspheres. We classify them into three categories according to their characteristics. When the histogram of each category is replaced with the corresponding calculated value of the scattering coefficient, each category is mapped to a different scattering-coefficient region. It is expected that the proposed method could be used to investigate the optical characteristics of a biological sample from OCT images, which would be helpful for optical diagnostic and therapeutic applications.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2003.05a
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• pp.62-62
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• 2003

A statistical evaluation method was proposed to evaluate mechanical properties by using small specimens and nano-indentation for irradiation study. The method is empirically based on nano-indentation which values are statistically treated. The nano-indentation in function of indentation depth (h) is expressed using the variation factor V(h). Statistical parameters of the indentation are given by histograms. Analytical and experimental relation between histograms of phase dimension distribution and parameters V(h) and G(h) is considered using the condition of additivity of phases' microhardness. The method is applied to estimate mechanical properties of irradiated materials.

• The Bulletin of The Korean Astronomical Society
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• v.31 no.1
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• pp.36-36
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• 2006

• Bulletin of the Korean Space Science Society
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• 2006.04a
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• pp.27-27
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• 2006

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.483-503
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• 2014

In this paper, human action recognition using pyramid histograms of oriented gradients and collaborative multi-task learning is proposed. First, we accumulate global activities and construct motion history image (MHI) for both RGB and depth channels respectively to encode the dynamics of one action in different modalities, and then different action descriptors are extracted from depth and RGB MHI to represent global textual and structural characteristics of these actions. Specially, average value in hierarchical block, GIST and pyramid histograms of oriented gradients descriptors are employed to represent human motion. To demonstrate the superiority of the proposed method, we evaluate them by KNN, SVM with linear and RBF kernels, SRC and CRC models on DHA dataset, the well-known dataset for human action recognition. Large scale experimental results show our descriptors are robust, stable and efficient, and outperform the state-of-the-art methods. In addition, we investigate the performance of our descriptors further by combining these descriptors on DHA dataset, and observe that the performances of combined descriptors are much better than just using only sole descriptor. With multimodal features, we also propose a collaborative multi-task learning method for model learning and inference based on transfer learning theory. The main contributions lie in four aspects: 1) the proposed encoding the scheme can filter the stationary part of human body and reduce noise interference; 2) different kind of features and models are assessed, and the neighbor gradients information and pyramid layers are very helpful for representing these actions; 3) The proposed model can fuse the features from different modalities regardless of the sensor types, the ranges of the value, and the dimensions of different features; 4) The latent common knowledge among different modalities can be discovered by transfer learning to boost the performance.

• The Journal of Korean Association of Computer Education
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• v.7 no.5
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• pp.111-120
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• 2004

The MPEG-7 standard defines a set of descriptors that extracts low-level features such as color, texture and object shape from an image and generates metadata in order to represent these extracted information. But the matching performance for image mining ma y not be satisfactory by u sing only on e of these features. Rather than by combining these features we can achieve a better query performance. In this paper we propose a new image retrieval technique for image mining that combines the features extracted from MPEG-7 visual color and texture descriptors. Specifically, we use only some specifications of Scalable Color Descriptor (SCD) and Non-Homogeneous Texture Descriptor also known as Edge Histogram Descriptor (EHD) for the implementation of the color and edge histograms respectively. MPEG-7 standard defines $l_{1}$-norm based matching in EHD and SCD. But in our approach, for distance measurement, we achieve a better result by using cosine similarity coefficient for color histograms and Euclidean distance for edge histograms. Our approach toward this system is more experimental based than hypothetical.