• Title/Summary/Keyword: automatic change extraction

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Automatic Coastline Extraction and Change Detection Monitoring using LANDSAT Imagery (LANDSAT 영상을 이용한 해안선 자동 추출과 변화탐지 모니터링)

  • Kim, Mi Kyeong;Sohn, Hong Gyoo;Kim, Sang Pil;Jang, Hyo Seon
    • Journal of Korean Society for Geospatial Information Science
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    • v.21 no.4
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    • pp.45-53
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    • 2013
  • Global warming causes sea levels to rise and global changes apparently taking place including coastline changes. Coastline change due to sea level rise is also one of the most significant phenomena affected by global climate change. Accordingly, Coastline change detection can be utilized as an indicator of representing global climate change. Generally, Coastline change has happened mainly because of not only sea level rise but also artificial factor that is reclaimed land development by mud flat reclamation. However, Arctic coastal areas have been experienced serious change mostly due to sea level rise rather than other factors. The purposes of this study are automatic extraction of coastline and identifying change. In this study, in order to extract coastline automatically, contrast of the water and the land was maximized utilizing modified NDWI(Normalized Difference Water Index) and it made automatic extraction of coastline possibile. The imagery converted into modified NDWI were applied image processing techniques in order that appropriate threshold value can be found automatically to separate the water and land. Then the coastline was extracted through edge detection algorithm and changes were detected using extracted coastlines. Without the help of other data, automatic extraction of coastlines using LANDSAT was possible and similarity was found by comparing NLCD data as a reference data. Also, the results of the study area that is permafrost always frozen below $0^{\circ}C$ showed quantitative changes of the coastline and verified that the change was accelerated.

Automatic Extraction of the Interest Organization from Full-Color Continuous Images for a Biological Sample

  • Takemoto, Satoko;Yokota, Hideo;Shimai, Hiroyuki;Makinouchi, Akitake;Mishima, Taketoshi
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.196-199
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    • 2002
  • We presented the automatic extraction technique of a biological internal organization from full-color continuous images. It was implemented using the localized homogeneousness of color intensity, and also using the continuity between neighboring images. Moreover, we set the "four-level status value" of area condition as a value showing "area possibility. This played important role of preventing a miss-judgement of area definition. These our approach had a beneficial effect on tracking color and shape change of the interest area in continuous extraction. As a resell we succeeded in extraction of mouse's stomach from continuous 50 images.

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An Effective Retinal Vessel and Landmark Detection Algorithm in RGB images

  • Jung Eun-Hwa
    • International Journal of Contents
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    • v.2 no.3
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    • pp.27-32
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    • 2006
  • We present an effective algorithm for automatic tracing of retinal vessel structure and vascular landmark extraction of bifurcations and ending points. In this paper we deal with vascular patterns from RGB images for personal identification. Vessel tracing algorithms are of interest in a variety of biometric and medical application such as personal identification, biometrics, and ophthalmic disorders like vessel change detection. However eye surface vasculature tracing in RGB images has many problems which are subject to improper illumination, glare, fade-out, shadow and artifacts arising from reflection, refraction, and dispersion. The proposed algorithm on vascular tracing employs multi-stage processing of ten-layers as followings: Image Acquisition, Image Enhancement by gray scale retinal image enhancement, reducing background artifact and illuminations and removing interlacing minute characteristics of vessels, Vascular Structure Extraction by connecting broken vessels, extracting vascular structure using eight directional information, and extracting retinal vascular structure, and Vascular Landmark Extraction by extracting bifurcations and ending points. The results of automatic retinal vessel extraction using jive different thresholds applied 34 eye images are presented. The results of vasculature tracing algorithm shows that the suggested algorithm can obtain not only robust and accurate vessel tracing but also vascular landmarks according to thresholds.

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A Study On Automatic Background Extraction and Updating Method (자동 배경 영상 추출 및 갱신 방법에 관한 연구)

  • 김덕래;하동문;김용득
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.35-38
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    • 2003
  • In this paper, I propose an automatic background extraction method and continuous background updating technique. Because there is a movement of a vehicle and a change of a background is feeble, the area moving through the time axis is looked for and a background and a vehicle image is divided. A way to give dynamically the threshold which divides the image frame into a vehicle image and the background in a space is enforced. Through the repetition of the above-mentioned process, the background pictorial image is gained. Using the karlman filter technique, the update is done so that a background image can obey a climate situation and an environmental change in day and night. A background image processed algorithm is better than the existent one. Through simulation, the feasibility of the algorithm has been verified.

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Mean-Shift Blob Clustering and Tracking for Traffic Monitoring System

  • Choi, Jae-Young;Yang, Young-Kyu
    • Korean Journal of Remote Sensing
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    • v.24 no.3
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    • pp.235-243
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    • 2008
  • Object tracking is a common vision task to detect and trace objects between consecutive frames. It is also important for a variety of applications such as surveillance, video based traffic monitoring system, and so on. An efficient moving vehicle clustering and tracking algorithm suitable for traffic monitoring system is proposed in this paper. First, automatic background extraction method is used to get a reliable background as a reference. The moving blob(object) is then separated from the background by mean shift method. Second, the scale invariant feature based method extracts the salient features from the clustered foreground blob. It is robust to change the illumination, scale, and affine shape. The simulation results on various road situations demonstrate good performance achieved by proposed method.

Korean Summarization System using Automatic Paragraphing (단락 자동 구분을 이용한 문서 요약 시스템)

  • 김계성;이현주;이상조
    • Journal of KIISE:Software and Applications
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    • v.30 no.7_8
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    • pp.681-686
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    • 2003
  • In this paper, we describes a system that extracts important sentences from Korean newspaper articles using automatic paragraphing. First, we detect repeated words between sentences. Through observation of the repeated words, this system compute Closeness Degree between Sentences(CDS ) from the degree of morphological agreement and the change of grammatical role. And then, it automatically divides a document into meaningful paragraphs using the number of paragraph defined by the user´s need. Finally. it selects one representative sentence from each paragraph and it generates summary using representative sentences. Though our system doesn´t utilize some features such as title, sentence position, rhetorical structure, etc., it is able to extract meaningful sentences to be included in the summary.

Proposal of Feature Classification System for Land Change Detection (국토변화탐지를 위한 지형분류체계 개선안)

  • Park, Jun-Ku;Noh, Myoung-Jong;Cho, Woo-Sug;Bang, Ki-In
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.2
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    • pp.9-17
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    • 2011
  • For the exact status of the land such as land cover classification and land use classification, feature classification system has been utilized in several organizations and agencies. However, those classification systems are limited to detection of land change and it's also not suited for the extraction of land changed. In this study, we would proposed a standard feature classification system which presents both in natural and artificial change of land effectively. Based on comparison and analysis of domestic and foreign relevant feature classification system, we proposed a standard feature classification system. In order to validate the applicability of the proposed feature classification system, we evaluated the accuracy with using automatic feature classification based on supervised classification and pre-knowledge hierarchical classification.

Robust Extraction of Facial Features under Illumination Variations (조명 변화에 견고한 얼굴 특징 추출)

  • Jung Sung-Tae
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.6 s.38
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    • pp.1-8
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    • 2005
  • Facial analysis is used in many applications like face recognition systems, human-computer interface through head movements or facial expressions, model based coding, or virtual reality. In all these applications a very precise extraction of facial feature points are necessary. In this paper we presents a method for automatic extraction of the facial features Points such as mouth corners, eye corners, eyebrow corners. First, face region is detected by AdaBoost-based object detection algorithm. Then a combination of three kinds of feature energy for facial features are computed; valley energy, intensity energy and edge energy. After feature area are detected by searching horizontal rectangles which has high feature energy. Finally, a corner detection algorithm is applied on the end region of each feature area. Because we integrate three feature energy and the suggested estimation method for valley energy and intensity energy are adaptive to the illumination change, the proposed feature extraction method is robust under various conditions.

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Intra-and Inter-frame Features for Automatic Speech Recognition

  • Lee, Sung Joo;Kang, Byung Ok;Chung, Hoon;Lee, Yunkeun
    • ETRI Journal
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    • v.36 no.3
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    • pp.514-517
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    • 2014
  • In this paper, alternative dynamic features for speech recognition are proposed. The goal of this work is to improve speech recognition accuracy by deriving the representation of distinctive dynamic characteristics from a speech spectrum. This work was inspired by two temporal dynamics of a speech signal. One is the highly non-stationary nature of speech, and the other is the inter-frame change of a speech spectrum. We adopt the use of a sub-frame spectrum analyzer to capture very rapid spectral changes within a speech analysis frame. In addition, we attempt to measure spectral fluctuations of a more complex manner as opposed to traditional dynamic features such as delta or double-delta. To evaluate the proposed features, speech recognition tests over smartphone environments were conducted. The experimental results show that the feature streams simply combined with the proposed features are effective for an improvement in the recognition accuracy of a hidden Markov model-based speech recognizer.

An automatic fault correction technique in the scene change detection by the key frame extraction includes multiple features (다중 특징을 포함한 키 프레임 추출에 의한 장면 전환 검출 오류 자동 수정 기법)

  • Yoon, Ju-Hyun;Youm, Sung-Ju;Kim, Woo-Saeng
    • Proceedings of the Korea Information Processing Society Conference
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    • 2002.04a
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    • pp.187-190
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    • 2002
  • 본 논문은 다중 특징을 포함한 대표 키 프레임을 추출을 통해 장면 전환 검출 시 발생할 수 있는 검출 오류를 자동으로 인식하고 수정함으로써 빠르고 신뢰성 있는 장면 분할을 수행하는 새로운 기법을 제안한다. 이를 위해 개선된 고속 장면 전환 검출 기법에 의해 샷을 분할 하고 분할 된 샷으로부터 대표 키 프레임과 그것에 포함된 후보 키 프레임들의 다중 정보를 포함시킴으로써 샷의 전반에 대한 정보를 보다 잘 표현할 수 있도록 한다. 그리고 다중정보를 포함한 대표 키 프레임의 비교를 통해 샷 검출 오류를 자동으로 인식하여 적절히 수정할 수 있는 기법을 제안하며 실세계 동영상 데이터를 사용한 실험을 통해서 제안하는 기법에 의해 효율적으로 샷이 분할 될 수 있음을 보인다.

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