• Title/Summary/Keyword: Contour Extraction

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Lightweight Single Image Super-Resolution Convolution Neural Network in Portable Device

  • Wang, Jin;Wu, Yiming;He, Shiming;Sharma, Pradip Kumar;Yu, Xiaofeng;Alfarraj, Osama;Tolba, Amr
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.11
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    • pp.4065-4083
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    • 2021
  • Super-resolution can improve the clarity of low-resolution (LR) images, which can increase the accuracy of high-level compute vision tasks. Portable devices have low computing power and storage performance. Large-scale neural network super-resolution methods are not suitable for portable devices. In order to save the computational cost and the number of parameters, Lightweight image processing method can improve the processing speed of portable devices. Therefore, we propose the Enhanced Information Multiple Distillation Network (EIMDN) to adapt lower delay and cost. The EIMDN takes feedback mechanism as the framework and obtains low level features through high level features. Further, we replace the feature extraction convolution operation in Information Multiple Distillation Block (IMDB), with Ghost module, and propose the Enhanced Information Multiple Distillation Block (EIMDB) to reduce the amount of calculation and the number of parameters. Finally, coordinate attention (CA) is used at the end of IMDB and EIMDB to enhance the important information extraction from Spaces and channels. Experimental results show that our proposed can achieve convergence faster with fewer parameters and computation, compared with other lightweight super-resolution methods. Under the condition of higher peak signal-to-noise ratio (PSNR) and higher structural similarity (SSIM), the performance of network reconstruction image texture and target contour is significantly improved.

Novel Intent based Dimension Reduction and Visual Features Semi-Supervised Learning for Automatic Visual Media Retrieval

  • kunisetti, Subramanyam;Ravichandran, Suban
    • International Journal of Computer Science & Network Security
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    • v.22 no.6
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    • pp.230-240
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    • 2022
  • Sharing of online videos via internet is an emerging and important concept in different types of applications like surveillance and video mobile search in different web related applications. So there is need to manage personalized web video retrieval system necessary to explore relevant videos and it helps to peoples who are searching for efficient video relates to specific big data content. To evaluate this process, attributes/features with reduction of dimensionality are computed from videos to explore discriminative aspects of scene in video based on shape, histogram, and texture, annotation of object, co-ordination, color and contour data. Dimensionality reduction is mainly depends on extraction of feature and selection of feature in multi labeled data retrieval from multimedia related data. Many of the researchers are implemented different techniques/approaches to reduce dimensionality based on visual features of video data. But all the techniques have disadvantages and advantages in reduction of dimensionality with advanced features in video retrieval. In this research, we present a Novel Intent based Dimension Reduction Semi-Supervised Learning Approach (NIDRSLA) that examine the reduction of dimensionality with explore exact and fast video retrieval based on different visual features. For dimensionality reduction, NIDRSLA learns the matrix of projection by increasing the dependence between enlarged data and projected space features. Proposed approach also addressed the aforementioned issue (i.e. Segmentation of video with frame selection using low level features and high level features) with efficient object annotation for video representation. Experiments performed on synthetic data set, it demonstrate the efficiency of proposed approach with traditional state-of-the-art video retrieval methodologies.

Analysis of Fish Activity in Relation to Feeding Events Using Infrared Cameras (적외선 카메라를 활용한 급이 유무에 따른 어류 활동성 분석)

  • Roh, Tae Kyoung;Ha, Sang Hyun;Kim, Ki Hwan;Kang, Young Jin;Jeong, Seok Chan
    • The Journal of Information Systems
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    • v.32 no.4
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    • pp.137-147
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    • 2023
  • Purpose The domestic aquaculture industry in South Korea utilizes both formulated feeds and live feeds for the cultivation of fish. While nutrient-rich live feeds, particularly using fry, have been preferred since the past, formulated feeds are gaining attention due to issues related to overfishing and environmental concerns. Formulated feeds are advantageous for storage and supply but require a sustained feeding regimen due to the comparatively slower growth rate compared to live feeds. As the aging population in rural areas leads to a shortage of labor, automated feeding systems are increasingly being adopted in aquaculture facilities. To enhance the efficiency of such systems, it is crucial to quantitatively analyze the behavioral changes in fish based on the presence or absence of feed. Design/methodology/approach In the study, RGB cameras and infrared cameras were used to analyze fish activity according to feeding, and an outline extraction algorithm was applied to analyze the differences resulting from this. Findings Unlike RGB cameras, infrared cameras are more suitable for analyzing underwater fish activity as they convert objects' thermal energy into images. It was observed that Canny, Sobel, and Prewitt filters showed the most distinct identification of fish activity.

Experimental Analysis of Algorithms of Splitting and Connecting Snake for Extracting of the Boundary of Multiple Objects (복수객체의 윤곽추출을 위한 스네이크 분리 및 연결 알고리즘의 실험적 분석)

  • Cui, Guo;Hwang, Jae-Yong;Jang, Jong-Whan
    • The KIPS Transactions:PartB
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    • v.19B no.4
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    • pp.221-224
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    • 2012
  • The most famous algorithm of splitting and connecting Snake for extracting the boundary of multiple objects is the nearest method using the distance between snake points. It often can't split and connect Snake due to object topology. In this paper, its problem was discussed experimentally. The new algorithm using vector between Snake segment is proposed in order to split and connect Snake with complicated topology of objects. It is shown by experiment of two test images with 3 and 5 objects that the proposed one works better than the nearest one.

A Study on Factor Extraction of Green-Network by Assessment Indicators -For the purpose of Biotop creation- (평가지표를 통한 녹지네트워크 인자도출에 관한 연구 -비오토프 조성을 위하여-)

  • Kim, E-Shin;Lee, Dong-Kun
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.4 no.3
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    • pp.75-83
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    • 2001
  • This study selected Yangpyung as a target site because Yangpyung is a area of high value blessed with well preserved natural resources and beautiful natural scene and where thoughtless development and malformed use of land are in progress under the mask of hotel, accommodations and sales facility which fits the interests of land owner. As for the method used for this study, I inquired into domestic/international instances and the concept of existing environmental indicators and assessment of suitability with a view to establish assessment indicators and pose the concept through theoretical investigation of green-network and to establish green-network. 17 articles of environmental indicators such as aspect analysis, contour, greenbelt, DEM, NDVI, nature conservation area, reservoir and area for the promotion of agriculture were chosen as a actual analysing n data for setting up assessment indicators. From the result of analysis, as anticipated, green zone in Yongmusan areas within Youngmun and Seojong areas were the center of green-network in the wide area green-network in Yangpyung and the restricted area by basin system, road and legal regulation was selected as spot area and finally arable land and reservoir were selected as base which connects core with spot.

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Neural Network-Based Human Identification Using Teeth Contours (치아 윤곽선 정보를 이용한 신경회로망 기반 신원 확인 방안)

  • Park, Sang-Jin;Park, Hyungjun
    • Korean Journal of Computational Design and Engineering
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    • v.18 no.4
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    • pp.275-282
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    • 2013
  • This paper proposes a method for human identification using teeth contours extracted from dental images that are captured from the frontal views of subjects each of who opens his or her mouth slightly. Each dental image has a black-colored region containing the subject's teeth contours which are usually different from subject to subject. This means that this black-colored region has bio-mimetic information useful for human identification. The basic idea of the method is to extract the upper and lower teeth contours from the dental image of each subject and to encode their geometric patterns using a back-propagation neural network model. After acquiring 400 teeth images form 10 university students, we used 300 images for the training data of the neural network model and 100 images for its verification. Experimental results have shown that the proposed neural network-based method can be used as an alternative solution for identification among a small group of humans with a low cost and simple setup.

Analysis of paper map images for acquiring 3D terrain data (3차원 지형 자료 획득을 위한 지도 영상 분석)

  • LEE, JIN SEON
    • Journal of the Korea Computer Graphics Society
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    • v.2 no.1
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    • pp.68-76
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    • 1996
  • One of the major problems in GIS(Geographical Information Systems) involves acquiring 3-D terrain data. Because conventional methods such as land surveying or analysis of aerial photographs are costly, the method of using existing paper maps has been gaining considerable attention. This method demands three processing steps: 1) extraction of contours, 2) assignment of height values to the extracted contours, 3) reconstruction of 3-D terrain data. In this paper we systematically develop a procedure for acquiring 3-D terrain data from contour solutions. For the first two steps, we describe the necessary operations and roughly sketch solutions. For the last step, we propose an efficient raster-based algorithm and present the results of experiments with existing paper map images.

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Recognition of the Passport by Using Fuzzy Binarization and Enhanced Fuzzy Neural Networks

  • Kim, Kwang-Baek
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.603-607
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    • 2003
  • The judgment of forged passports plays an important role in the immigration control system, for which the automatic and accurate processing is required because of the rapid increase of travelers. So, as the preprocessing phase for the judgment of forged passports, this paper proposed the novel method for the recognition of passport based on the fuzzy binarization and the fuzzy RBF neural network newly proposed. first, for the extraction of individual codes being recognized, the paper extracts code sequence blocks including individual codes by applying the Sobel masking, the horizontal smearing and the contour tracking algorithm in turn to the passport image, binarizes the extracted blocks by using the fuzzy binarization based on the membership function of trapezoid type, and, as the last step, recovers and extracts individual codes from the binarized areas by applying the CDM masking and the vertical smearing. Next, the paper proposed the enhanced fuzzy RBF neural network that adapts the enhanced fuzzy ART network to the middle layer and applied to the recognition of individual codes. The results of the experiment for performance evaluation on the real passport images showed that the proposed method in the paper has the improved performance in the recognition of passport.

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Esthetic reconstruction of upper central incisor using immediate Frialit-2 implant placement, immediate temporary crown fabrication and IPS Empress 2 crown (즉시 Frialit-2 implant 식립, 즉시 임시치관 제작 그리고 IPS Empress 2 crown을 이용한 상악중절치의 심미적 수복)

  • Kim, Yu-Lee;Oh, Sang-Chun
    • Journal of Dental Rehabilitation and Applied Science
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    • v.19 no.1
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    • pp.43-48
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    • 2003
  • During the past several years, significant advances have occurred in the utilization of osseointegrated implants for the treatment of partially edentulous patients. One of the biggest purposes for treating of these patients is the high demand for improved esthetics, especially in the anterior region. For this esthetics, the new trend in dental implants is the immediate placement and immediate superstructure fabrication. The refined surgical technique, the skillful soft tissue management, and the proper prosthetic coordination are the main factors to achieve natural looking of implant supported prosthesis. The customized provisional restoration and the customized impression coping are recommended for the optimal peri-implant soft tissue contour. The basic concept of Frialit 2 system was the immediate replacement of a tooth with root-analog fixture after extraction. This system guarantees an ideal result in function and esthetics. The ceramic abutment system offers improved quality in the respect of esthetics, fitness, translucency, and biocompatibility. In this clinical report, the final restoration made with IPS Empress 2 crown on the CeraBase abutmen of Frialit 2 system allowed the reproduction of the natural vitality of tooth and adjacent gingiva.

Passport Recognition using Fuzzy Binarization and Enhanced Fuzzy RBF Network

  • Kim, Kwang-Baek
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.2
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    • pp.222-227
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    • 2004
  • Today, an automatic and accurate processing using computer is essential because of the rapid increase of travelers. The determination of forged passports plays an important role in the immigration control system. Hence, as the preprocessing phase for the determination of forged passports, this paper proposes a novel method for the recognition of passports based on the fuzzy binarization and the fuzzy RBF network. First, for the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Then the proposed method binarizes the extracted blocks using fuzzy binarization based on the trapezoid type membership function. Then, as the last step, individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an enhanced fuzzy RBF network that adapts the enhanced fuzzy ART network for the middle layer. This network is applied to the recognition of individual codes. The results of the experiments for performance evaluation on the real passport images showed that the proposed method has the better performance compared with other approaches.