• Title/Summary/Keyword: image search

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Improved Statistical Grey-Level Models for PCB Inspection (PCB 검사를 위한 개선된 통계적 그레이레벨 모델)

  • Bok, Jin Seop;Cho, Tai-Hoon
    • Journal of the Semiconductor & Display Technology
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    • v.12 no.1
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    • pp.1-7
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    • 2013
  • Grey-level statistical models have been widely used in many applications for object location and identification. However, conventional models yield some problems in model refinement when training images are not properly aligned, and have difficulties for real-time recognition of arbitrarily rotated models. This paper presents improved grey-level statistical models that align training images using image or feature matching to overcome problems in model refinement of conventional models, and that enable real-time recognition of arbitrarily rotated objects using efficient hierarchical search methods. Edges or features extracted from a mean training image are used for accurate alignment of models in the search image. On the aligned position and orientation, fitness measure based on grey-level statistical models is computed for object recognition. It is demonstrated in various experiments in PCB inspection that proposed methods are superior to conventional methods in recognition accuracy and speed.

Fast fractal coding based on correlation coefficients of subblocks in input image (입력 영상의 서브블록들 사이의 상관관계에 기반한 고속 프랙탈 부호화)

  • 배수정;임재권
    • Proceedings of the IEEK Conference
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    • 1998.06a
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    • pp.669-672
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    • 1998
  • In this paper, w epropose a fast fractal coding method based on correlation coefficients of subblocks in input image. In the proposed method, domain pool is selected based on correlation analysis of input image and the isometry transform for each block is chosen based on the IFS method. To investigate the performance of the proposed method, we compared image quality and encoding time with full search PIFS method and jacquin's PIFS method. Experimental results show that proposed method yields nearly the same performance in PSNR, and its encoding time is reduced for images size of 512*512 compared with full search PIFS method and jacquin's PIFS method.

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3 Dimensional Augmented Reality Flight for Drones

  • Park, JunMan;Kang, KiBeom;Jwa, JeongWoo;Won, JoongHie
    • International Journal of Internet, Broadcasting and Communication
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    • v.10 no.2
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    • pp.13-18
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    • 2018
  • Drones are controlled by the remote pilot from the ground stations using the radio control or autonomously following the pre-programmed flight plans. In this paper, we develop a method and an optimal path search system for providing 3D augmented reality flight (ARF) images for safe and efficient flight control of drones. The developed system consisted of the drone, the ground station and user terminals, and the optimal path search server. We use the Dijkstra algorithm to find the optimal path considering the drone information, flight information, environmental information, and flight mission. We generate a 3D augmented reality flight (ARF) image overlaid with the path information as well as the drone information and the flight information on the flight image received from the drone. The ARF image for adjusting the drone is generated by overlaying route information, drone information, flight information, and the like on the image captured by the drone.

The Improved Watershed Algorithm using Adaptive Local Threshold (적응적 지역 임계치를 이용한 개선된 워터쉐드 알고리즘)

  • Lee Seok-Hee;Kwon Dong-Jin;Kwak Nae-Joung;Ahn Jae-Hyeong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2004.11a
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    • pp.891-894
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    • 2004
  • This paper proposes an improved image segmentation algorithm by the watershed algorithm based on the local adaptive threshold on local minima search and the fixing threshold on label allocation. The previous watershed algorithm generates the problem of over-segmentation. The over-segmentation makes the boundary in the inaccuracy region by occurring around the object. In order to solve those problems we quantize the input color image by the vector quantization, remove noise and find the gradient image. We sorted local minima applying the local adaptive threshold on local minima search of the input color image. The simulation results show that the proposed algorithm controls over-segmentation and makes the fine boundary around segmented region applying the fixing threshold based on sorted local minima on label allocation.

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Vignetting Dimensional Geometric Models and a Downhill Simplex Search

  • Kim, Hyung Tae;Lee, Duk Yeon;Choi, Dongwoon;Kang, Jaehyeon;Lee, Dong-Wook
    • Current Optics and Photonics
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    • v.6 no.2
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    • pp.161-170
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    • 2022
  • Three-dimensional (3D) geometric models are introduced to correct vignetting, and a downhill simplex search is applied to determine the coefficients of a 3D model used in digital microscopy. Vignetting is nonuniform illuminance with a geometric regularity on a two-dimensional (2D) image plane, which allows the illuminance distribution to be estimated using 3D models. The 3D models are defined using generalized polynomials and arbitrary coefficients. Because the 3D models are nonlinear, their coefficients are determined using a simplex search. The cost function of the simplex search is defined to minimize the error between the 3D model and the reference image of a standard white board. The conventional and proposed methods for correcting the vignetting are used in experiments on four inspection systems based on machine vision and microscopy. The methods are investigated using various performance indices, including the coefficient of determination, the mean absolute error, and the uniformity after correction. The proposed method is intuitive and shows performance similar to the conventional approach, using a smaller number of coefficients.

A Study on Market Segmentation through Clothes Image Preferences and Benefit (Part I) (선호 의복이미지와 편익에 의한 시장세분화에 관한 연구(제1보))

  • 이숙희;임숙자
    • Journal of the Korean Society of Clothing and Textiles
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    • v.27 no.1
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    • pp.100-110
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    • 2003
  • The purpose of this study were 1) to find out the structural elements in classifying clothes images, and 2) to segment the consumer market for women's street clothes based on clothes image preferences and to identify the group differences in psychological variables, purchasing behavior variables and demographic variables. The sample was taken from 1106 middle class women who were in thier 30's∼40's living in Gwangju city. Consumers were classified into six groups: active image group (35.4%), feminine image group (25.9%). daring image group (16.5%), elegant image group (10.8%), dressy image group (8.9%) and brisk image group (3.5%). Women in their 30's∼40's preferred elegant image, daring image, active image and feminine image. Elegant image oriented group: This group is the lowest education level group and has the highest rating of housewife. This group has the lowest scores use of person information search, Daring image oriented group: Woman in their 30's prefers daring image. This group thinks practical benefit sought is less important than self-expression benefit sought. This group has the highest scores use of non-person information search, Active image oriented group: This group is practical benefit seeking group. and purchases the lowest amount of clothes. The amount of average household income is the lowest. Feminine image oriented group: The amount of average household income is the highest. This group perceives more youth$.$fashion benefit sought and self-expression benefit sought than elegant image oriented group. ANOVA, $\chi$$^2$-test revealed differences among groups according to benefit sought use of information sources, purchasing behavior variables and demographic variables.

A Design for Efficient Similar Subsequence Search with a Priority Queue and Suffix Tree in Image Sequence Databases (이미지 시퀀스 데이터베이스에서 우선순위 큐와 접미어 트리를 이용한 효율적인 유사 서브시퀀스 검색의 설계)

  • 김인범
    • Journal of the Korea Computer Industry Society
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    • v.4 no.4
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    • pp.613-624
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    • 2003
  • This paper proposes a design for efficient and accurate retrieval of similar image subsequences using the multi-dimensional time warping distance as similarity evaluation tool in image sequence database after building of two indexing structures implemented with priority queue and suffix tree respectively. Receiving query image sequence, at first step, the proposed method searches the candidate set of similar image subsequences in priory queue index structure. If it can not get satisfied results, it retrieves another candidate set in suffix tree index structure at second step. The using of the low-bound distance function can remove the dissimilar subsequence without false dismissals during similarity evaluating process between query image sequence and stored sequences in two index structures.

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Image Description and Matching Scheme Using Synthetic Features for Recommendation Service

  • Yang, Won-Keun;Cho, A-Young;Oh, Weon-Geun;Jeong, Dong-Seok
    • ETRI Journal
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    • v.33 no.4
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    • pp.589-599
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    • 2011
  • This paper presents an image description and matching scheme using synthetic features for a recommendation service. The recommendation service is an example of smart search because it offers something before a user's request. In the proposed extraction scheme, an image is described by synthesized spatial and statistical features. The spatial feature is designed to increase the discriminability by reflecting delicate variations. The statistical feature is designed to increase the robustness by absorbing small variations. For extracting spatial features, we partition the image into concentric circles and extract four characteristics using a spatial relation. To extract statistical features, we adapt three transforms into the image and compose a 3D histogram as the final statistical feature. The matching schemes are designed hierarchically using the proposed spatial and statistical features. The result shows that each feature is better than the compared algorithms that use spatial or statistical features. Additionally, if we adapt the proposed whole extraction and matching scheme, the overall performance will become 98.44% in terms of the correct search ratio.

Digital Image Comparisons for Investigating Aging Effects and Artificial Modifications Using Image Analysis Software

  • Yoo, Yeongsik;Yoo, Woo Sik
    • Journal of Conservation Science
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    • v.37 no.1
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    • pp.1-12
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    • 2021
  • In the digital era, large archives of information and Internet accessibility make information search, including image search, easier and affordable, even from remote locations. Information transmission and sharing can be performed instantly, at any moment. In the case of images, there are risks of transmitting and recklessly sharing intentionally modified images. Such modified images can also be transmitted and used as an additional source of information by followers. In this study, historical portraits of Yu Kil-Chun are shown, who was the first Korean student to study in both Japan and the United States. He was an intellectual, writer, politician, and independence activist of Korea's late Joseon Dynasty. Using image processing software, the portrait images were compared to investigate aging effects and artificial modifications. Statistics of red (R), green (G), blue (B), and L*, a*, and b* values of every pixel in the selected identical areas of the portraits were compared to identify possible causes of variations, including aging effects and artificial modifications. Sepia toning, used in black and white photographs until the 1930s, and modern digital sepia toning can be very confusing owing to their aging effects. The importance of preservation of physical copies and preservation of context (interconnections between data and between documents) is discussed from archiving and conservation science perspectives.

Accurate Detection of a Defective Area by Adopting a Divide and Conquer Strategy in Infrared Thermal Imaging Measurement

  • Jiangfei, Wang;Lihua, Yuan;Zhengguang, Zhu;Mingyuan, Yuan
    • Journal of the Korean Physical Society
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    • v.73 no.11
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    • pp.1644-1649
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    • 2018
  • Aiming at infrared thermal images with different buried depth defects, we study a variety of image segmentation algorithms based on the threshold to develop global search ability and the ability to find the defect area accurately. Firstly, the iterative thresholding method, the maximum entropy method, the minimum error method, the Ostu method and the minimum skewness method are applied to image segmentation of the same infrared thermal image. The study shows that the maximum entropy method and the minimum error method have strong global search capability and can simultaneously extract defects at different depths. However none of these five methods can accurately calculate the defect area at different depths. In order to solve this problem, we put forward a strategy of "divide and conquer". The infrared thermal image is divided into several local thermal maps, with each map containing only one defect, and the defect area is calculated after local image processing of the different buried defects one by one. The results show that, under the "divide and conquer" strategy, the iterative threshold method and the Ostu method have the advantage of high precision and can accurately extract the area of different defects at different depths, with an error of less than 5%.