• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.3
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• pp.451-456
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• 2017

Semantic segmentation, which is the most basic and complicated problem in computer vision, classifies each pixel of an image into a specific object and performs a task of specifying a label. MRF and CRF, which have been studied in the past, have been studied as effective methods for improving the accuracy of pixel level labeling. In this paper, we propose a semantic partitioning method that combines CNN, a kind of deep running, which is in the spotlight recently, and CRF, a probabilistic model. For learning and performance verification, Pascal VOC 2012 image database was used and the test was performed using arbitrary images not used for learning. As a result of the study, we showed better partitioning performance than existing semantic partitioning algorithm.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.149-156
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• 2011

This paper proposes the effective edge selection algorithm for the rapid processing time and low memory usage of efficient graph-based image segmentation on mobile device. The graph-based image segmentation algorithm is to extract objects from a single image. The objects are consisting of graph edges, which are created by information of each image's pixel. The edge of graph is created by the difference of color intensity between the pixel and neighborhood pixels. The object regions are found by connecting the edges, based on color intensity and threshold value. Therefore, the number of edges decides on the processing time and amount of memory usage of graph-based image segmentation. Comparing to personal computer, the mobile device has many limitations such as processor speed and amount of memory. Additionally, the response time of application is an issue of mobile device programming. The image processing on mobile device should offer the reasonable response time, so that, the image segmentation processing on mobile should provide with the rapid processing time and low memory usage. In this paper, we demonstrate the performance of the effective edge selection algorithm, which effectively controls the edges of graph for the rapid processing time and low memory usage of graph-based image segmentation on mobile device.

• Proceedings of the KAIS Fall Conference
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• 2012.05b
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• pp.531-534
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• 2012

본 논문에서는 Active Contour 기반의 영역 분할에서 이미지의 초점값을 이용하여 분할된 영역 사이의 경계를 생성하여 기존의 Active Contour에서 발생할 수 있는 중첩 객체의 동일 객체 인식을 방지하는 기법을 제안한다. Active Contour는 영상에서 객체의 윤곽을 검출하여 윤곽을 기준으로 영상을 분할하지만 중첩되거나 근접한 객체에서의 분할이 정확하게 이루어지지 않아 동일 객체로 인식하는 단점이 있다. 이러한 객체에서의 분할을 위해 영상의 초점값을 이용하여 영상 내에 존재하는 객체의 유사 경계 영역을 생성하고 Active Contour의 결과에 적용하여 경계를 생성한 뒤 초점값 적용으로 인해 생성될 수 있는 홀 영역을 hole filling 과정을 수행하여 보완함으로써 보다 정확한 객체를 추출하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.81-83
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• 2021

In this paper, we propose a method to segment a plant from a plant image using U-Net. The network is an end-to-end fully convolutional network that is mainly used for image segmentation. When training the network, we used a binary image that is acquired by the manual segmentation of a plant from the background. Experimental results show that the U-Net based segmentation network can extract a plant from a digital image accurately.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.169-175
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• 2011

In this paper, an automatic scoring system of the OMR answer sheet is implemented using Gray Scale and image segmentation method. The proposed method was used to extract the OMR data on multiple-choice answer sheet from captured image. In addition, On-line scoring system is developed and implemented to mark the short-answer type on the reverse side. Therefore, teachers can mark the short-answer type for anytime and anywhere within the available time. There were many advantages to mark of the multiple-choice answer sheet without additional OMR reader. In the future, the grading of short-answer type will be more efficient if it were performed by using an automatic scoring system based on image processing.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.3
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• pp.201-207
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• 2008

This paper presents the implementation of a Tiling System about Preprocessing functions of JPEG 2000. The system covers the JPEG 2000 standard and is designed to determine the size of the image, to expand the image area and to split input image into several tiles. In order to split the input image with the progressive transmission into several tiles and transmit a tile of this image to others, this system store this image into Frame Memory. Therefore, this is designed as the Finite State Machine (FSM) to sequence through specific patterns of states in a predetermined sequential manner by using Verilog-HDL and be designed to handle a maximum 5M image. Moreover, for identifying image size for expansion, we propose several formula which are based on remainder after division (rem). we propose the true table which determines the size of the image input patterns by using results of these formula. Under the condition of TSMC 0.25um ASIC library, gate count is 18,725 and maximum data arrival time is 18.94 [ns].

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.5
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• pp.628-638
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• 1999

In this paper, we presents a method of retrieving 24 bpp RGB images based on color-spatial features. For each image, it is subdivided into regions by using similarity of color after converting RGB color space to CIE L*u*v* color space that is perceptually uniform. Our segmentation algorithm constrains the size of region because a small region is discardable and a large region is difficult to extract spatial feature. For each region, averaging color and center of region are extracted to construct color-spatial features. During the image retrieval process, the color and spatial features of query are compared with those of the database images using our similarity measure to determine the set of candidate images to be retrieved. We implement a content-based color image retrieval system using the proposed method. The system is able to retrieve images by user graphic or example image query. Experimental results show that Recall/Precision is 0.80/0.84.

• Journal of Creative Information Culture
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• v.6 no.1
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• pp.41-48
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• 2020

In order to represent and process spatial data, hierarchical data structures such as a quadtree or a bintree are used. Various approaches for linearly representing the bintree have been proposed. S-Tree has the advantage of compressing the storage space by expressing binary region image data as a linear binary bit stream, but the higher the resolution of the image, the longer the length of the binary bit stream, the longer the storage space and the lower the search performance. In this paper, we construct a hierarchical structure of multiple separated bintrees with a full binary tree structure and express each bintree as two linear binary bit streams to reduce the range required for image search. It improves the overall search performance by performing a simple number conversion instead of searching directly the binary bit string path. Through the performance evaluation by the worst-case space-time complexity analysis, it was analyzed that the proposed method has better search performance and space efficiency than the previous one.

• Journal of The Korean Association For Science Education
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• v.40 no.1
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• pp.13-28
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• 2020

This study attempted to understand the characteristics of images of scientific experiments represented and consumed on YouTube, a representative of today's new media. In particular, this paper analyzes the case studies of YouTube's hydrogen peroxide decomposition experiment based on Baudrillard's theory of Simulation and Simulacra, which discusses the strong status of images and the ambiguity of the boundary between virtual and reality. A total of 14 YouTube videos related to hydrogen peroxide decomposition experiments were analyzed. In those videos, hydrogen peroxide decomposition experiments were typically conducted with several signs representing scientific experiments, but the most important sign in the videos were bubbles produced through experiments. For more public consumption of the content, the bubbles resulted from hydrogen peroxide decomposition reproduced in YouTube have been transformed into a more spectacular image as 'super-huge' and 'explosive' bubble. Considering the influence of new media that can be accessed by students anytime and anywhere, it is positive that science experiments in new media enhance students' intimacy and access to science. At the same time, however, it is also important to note the danger that the purpose of scientific experiments will be limited to only 'showing specular images', due to the nature of new media, which mainly deals with immediate and superficial images. Furthermore, this study argues that improving students' science media literacy is required to critically examine the science-related images represented in the new media based on understanding the characteristics and limitations of new media that deeply affect daily life.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.331-332
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• 2024

최근 디지털 워터마킹 기술은 디지털 콘텐츠의 저작권 보호 및 추적을 위해 활용되고 있다. 그러나 종래의 워터마킹 기술은 이미지에 워터마크 이미지 전체를 삽입하기 때문에 왜곡 공격에 취약하다. 이러한 문제를 해결하기 위해 본 연구에서는 워터마크 분할 삽입 기법을 제안하였다. 워터마크 분할 삽입 기법을 사용하면 종래 방법 대비 20%p의 손실률이 증가하더라도 원본 워터마크를 복구할 수 있어 1.5배 향상된 성능을 보인다.