• Title/Summary/Keyword: Directional filtering

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A Study on NPC Grouping of 3D Game using Gabor Characteristics (가버 특성을 이용한 3D 게임의 NPC 그룹핑에 관한 연구)

  • Park, Chang-Min
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.12
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    • pp.2836-2842
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    • 2010
  • An NPC grouping method is proposed for various 3D games depending on their characteristics. Immovable objects tend to have particular orientation features in their Gabor filtering results whereas the movable objects controlled by AI appearing as a human or an animal do not. First of all, We analyzed directional and frequency domain features in the NPC object and configured them as 24 Gabor filter banks. Then, 24-dimensional feature vectors according to the scale and direction of the filter are calculated. Each extracted vector represents the energy of a certain direction. This energy indicates the particular direction strength of the object texture. Thus, using this property, NPCs could be grouped as artificial objects and natural objects effectively and it draws the game more speed and strategic actions as a result.

Content Recommendation Techniques for Personalized Software Education (개인화된 소프트웨어 교육을 위한 콘텐츠 추천 기법)

  • Kim, Wan-Seop
    • Journal of Digital Convergence
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    • v.17 no.8
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    • pp.95-104
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    • 2019
  • Recently, software education has been emphasized as a key element of the fourth industrial revolution. Many universities are strengthening the software education for all students according to the needs of the times. The use of online content is an effective way to introduce SW education for all students. However, the provision of uniform online contents has limitations in that it does not consider individual characteristics(major, sw interest, comprehension, interests, etc.) of students. In this study, we propose a recommendation method that utilizes the directional similarity between contents in the boolean view history data environment. We propose a new item-based recommendation formula that uses the confidence value of association rule analysis as the similarity level and apply it to the data of domestic paid contents site. Experimental results show that the recommendation accuracy is improved than when using the traditional collaborative recommendation using cosine or jaccard for similarity measurements.

Postprocessing of Inter-Frame Coded Images Based on Convex Projection and Regularization (POCS와 정규화를 기반으로한 프레임간 압출 영사의 후처리)

  • Kim, Seong-Jin;Jeong, Si-Chang;Hwang, In-Gyeong;Baek, Jun-Gi
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.3
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    • pp.58-65
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    • 2002
  • In order to reduce blocking artifacts in inter-frame coded images, we propose a new image restoration algorithm, which directly processes differential images before reconstruction. We note that blocking artifact in inter-frame coded images is caused by both 8$\times$8 DCT and 16$\times$16 macroblock based motion compensation, while that of intra-coded images is caused by 8$\times$8 DCT only. According to the observation, we Propose a new degradation model for differential images and the corresponding restoration algorithm that utilizes additional constraints and convex sets for discontinuity inside blocks. The proposed restoration algorithm is a modified version of standard regularization that incorporate!; spatially adaptive lowpass filtering with consideration of edge directions by utilizing a part of DCT coefficients. Most of video coding standard adopt a hybrid structure of block-based motion compensation and block discrete cosine transform (BDCT). By this reason, blocking artifacts are occurred on both block boundary and block interior For more complete removal of both kinds of blocking artifacts, the restored differential image must satisfy two constraints, such as, directional discontinuities on block boundary and block interior Those constraints have been used for defining convex sets for restoring differential images.

Enhanced Recovery of Gravity Fields from Dense Altimeter Data

  • Kim, Jeong-Hee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.14 no.2
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    • pp.127-139
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    • 1996
  • This paper presents a procedure to recover sea surface heights (SSH) and free-air (FA) gravity anomalies from dense satellite altimeter SSH data with enhanced accuracies over the full spectrum of the gravity field. A wavenumber correlation filtering (WCF) of co-linear SSH tracks is developed for the coherent signals of sub-surface geological masses. Orbital cross-over adjustments with bias parameters are applied to the filtered SSH data, which are then separated into two groups of ascending and descending tracks and gridded with tensioned splines. A directional sensitive filter (DSF) is developed to reduce residual errors in the orbital adjustments that appear as track patterned SSH. Finally, FA gravity anomalies can be obtained by the application of a gradient filter on a high resolution estimate of geoid undulations after subtracting dynamic sea surface topography (DSST) from the SSH. These procedures are applied to the Geosat Geodetic Mission (GM) data of the southern oceans in a test area of ca. $900km\;\times{1,200}\;km$ to resolve geoid undulations and FA gravity anomalies to wavelengths of-10 km and larger. Comparisons with gravity data from ship surveys, predictions by least squares collocation (LSC), and 2 versions of NOAA's predictions using vertical deflections illustrate the performance of this procedure for recovering all elements of the gravity spectrum. Statistics on differences between precise ship data and predicted FA gravity anomalies show a mean of 0.1 mgal, an RMS of 3.5 mgal, maximum differences of 10. 2 mgal and -18.6 mgal, and a correlation coefficient of 0.993 over four straight ship tracks of ca. 1,600 km where gravity changes over 150 mgals.

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Speech extraction based on AuxIVA with weighted source variance and noise dependence for robust speech recognition (강인 음성 인식을 위한 가중화된 음원 분산 및 잡음 의존성을 활용한 보조함수 독립 벡터 분석 기반 음성 추출)

  • Shin, Ui-Hyeop;Park, Hyung-Min
    • The Journal of the Acoustical Society of Korea
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    • v.41 no.3
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    • pp.326-334
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    • 2022
  • In this paper, we propose speech enhancement algorithm as a pre-processing for robust speech recognition in noisy environments. Auxiliary-function-based Independent Vector Analysis (AuxIVA) is performed with weighted covariance matrix using time-varying variances with scaling factor from target masks representing time-frequency contributions of target speech. The mask estimates can be obtained using Neural Network (NN) pre-trained for speech extraction or diffuseness using Coherence-to-Diffuse power Ratio (CDR) to find the direct sounds component of a target speech. In addition, outputs for omni-directional noise are closely chained by sharing the time-varying variances similarly to independent subspace analysis or IVA. The speech extraction method based on AuxIVA is also performed in Independent Low-Rank Matrix Analysis (ILRMA) framework by extending the Non-negative Matrix Factorization (NMF) for noise outputs to Non-negative Tensor Factorization (NTF) to maintain the inter-channel dependency in noise output channels. Experimental results on the CHiME-4 datasets demonstrate the effectiveness of the presented algorithms.

Recognition of Resident Registration Card using ART2-based RBF Network and face Verification (ART2 기반 RBF 네트워크와 얼굴 인증을 이용한 주민등록증 인식)

  • Kim Kwang-Baek;Kim Young-Ju
    • Journal of Intelligence and Information Systems
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    • v.12 no.1
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    • pp.1-15
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    • 2006
  • In Korea, a resident registration card has various personal information such as a present address, a resident registration number, a face picture and a fingerprint. A plastic-type resident card currently used is easy to forge or alter and tricks of forgery grow to be high-degree as time goes on. So, whether a resident card is forged or not is difficult to judge by only an examination with the naked eye. This paper proposed an automatic recognition method of a resident card which recognizes a resident registration number by using a refined ART2-based RBF network newly proposed and authenticates a face picture by a template image matching method. The proposed method, first, extracts areas including a resident registration number and the date of issue from a resident card image by applying Sobel masking, median filtering and horizontal smearing operations to the image in turn. To improve the extraction of individual codes from extracted areas, the original image is binarized by using a high-frequency passing filter and CDM masking is applied to the binaried image fur making image information of individual codes better. Lastly, individual codes, which are targets of recognition, are extracted by applying 4-directional contour tracking algorithm to extracted areas in the binarized image. And this paper proposed a refined ART2-based RBF network to recognize individual codes, which applies ART2 as the loaming structure of the middle layer and dynamicaly adjusts a teaming rate in the teaming of the middle and the output layers by using a fuzzy control method to improve the performance of teaming. Also, for the precise judgement of forgey of a resident card, the proposed method supports a face authentication by using a face template database and a template image matching method. For performance evaluation of the proposed method, this paper maked metamorphoses of an original image of resident card such as a forgey of face picture, an addition of noise, variations of contrast variations of intensity and image blurring, and applied these images with original images to experiments. The results of experiment showed that the proposed method is excellent in the recognition of individual codes and the face authentication fur the automatic recognition of a resident card.

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