• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.127-136
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• 2008

A digitized image passes by encoding, storing or transmitting to show it to users. In this process, may be users would want to see a specific region of the image. And depending on the system features or in the case that the resolution of the image is large, it will take a huge time that the image show to the users. In this time, it will be resonable that the part users want to see shows earlier and afterward the other parts show. For this, JPEG2000 standards provide ROI. Although ROI extraction that users specify ROI arbitrarily is the best, people not always participate in doing all the images. There needs an automatic ROI extracting and storing in some images. JPEG2000 should extract and send an ROI automatically when the images is encoded without ROI. This study proposes a method that automatically extracts an ROI, makes the ROI masks, transfers the masked image preferentially and the background. And the study compares and experiments the proposed method and the method not having ROI.

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.275-302
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• 2007

We propose a novel still image compression system which supports a high quality text compression function. The system segments the text from the image and compresses the text with a high quality. The system shows 48:1 high compression ratio using context-based adaptive binary arithmetic coding. The arithmetic coding performs the high compression by the codeblocks in the bitplane. The input of the system consists of a segmentation mode and a ROI(Region Of Interest) mode. In segmentation mode, the input image is segmented into a foreground consisting of text and a background consisting of the remaining region. In ROI mode, the input image is represented by the region of interest window. The high quality text compression function with a high compression ratio shows that the proposed system can be comparable with the JPEG2000 products. This system also uses gray coding to improve the compression ratio.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.411-420
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• 2004

We propose a novel still image compression system, which is superior in its function than the JPEG2000 system developed by David Taubman. The system shows 40 : 1 high compression ratio using $2\times2$ bitmatrix subblock coding. The $2\times2$ bitmatrix subblock is constructed in the bitplanes by organizing the bits into subblocks composing of $2\times2$matrices. The arithmetic coding performs the high compression by the bitmatrices in the subblock. The input of the system consists of a segmentation mode and a ROI(Region Of Interest) mode. In segmentation mode, the input image is segmented into a foreground consisting of letters and a background consisting of the remaining region. In ROI mode, the input image is represented by the region of interest window. The high compression ratio shows that the proposed system is competent among the JPEG2000 products currently in the market. This system also uses gray coding to improve the compression ratio.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.679-686
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• 2014

Recently, users can get countless images and videos by network. So, the compression technology of image and video is researched more and more. However, the situation which is the interested range of the image is occurred. For instance, since the region of face is more important than background, the image compression technology bases on the region of interest (ROI) is necessary, in the ATM environment. In this research, given the human visual system, which are not sensitive to illumination variations at very dark and light regions of image, we calculate the standard deviation of block and use this value to define the ROI. In encoding process, the relatively high quality can be obtained at the ROI and the relatively low quality can be obtained at the non ROI. In proposed scheme, the feature which is the encoding process according to subjectively image quality can be demonstrated. Finally, this proposed scheme is applied to JPEG standard. The experimental results demonstrate that proposed scheme can achieve better image quality at the high compression ratio.

• Journal of Korea Multimedia Society
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• v.11 no.5
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• pp.588-596
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• 2008

For the patients' privacy, secure access control of medical images is essentially necessary. In this paper, two types of Region of Interest (ROI)-based selective encryption schemes are proposed, which concentrate on the security of crucial parts in medical images. The first scheme randomly inverts the most significant bits of ROI coefficients in several high frequency subbands in the transform domain, which only incurs little loss on compression efficiency. The second scheme employs a symmetric key encryption to encrypt selectively the ROI data in the final code-stream, which provides sufficient confidentiality. Both of two schemes are backward compatible so as to ensure a standard bitstream compliant decoder so the encrypted images can be reconstructed without any crash.

• Journal of Digital Contents Society
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• v.12 no.1
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• pp.1-9
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• 2011

JPEG2000 offers the technique which compresses the interested regions with higher quality than the background. It is called by an ROI(Region-of-Interest) coding method. In this paper, we use images including the human faces, which are processed uppermost and compressed with high quality. The proposed method consists of 2 steps. The first step extracts some faces and the second one is ROI coding. To extract the faces, the method cuts or scale-downs some regions with $20{\times}20$ window pixels for all the pixels of the image, and after preprocessing, recognizes the faces using neural networks. Each extracted region is identified by ROI mask and then ROI-coded using Maxshift method. After then, the image is compressed and saved using EBCOT. The existing methods searched the ROI by edge distributions. On the contrary, the proposed method uses human intellect. And the experiment shows that the method is sufficiently useful with images having several human faces.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.3
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• pp.257-266
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• 2020

It is very important to share tactical information such as video, images, and text messages among soldiers for situational awareness. Under the wireless environment of the battlefield, the available bandwidth varies dynamically and is insufficient to transmit high quality images, so it is necessary to minimize the distortion of the area of interests such as targets. A natural operating method for soldiers is also required considering the difficulty in handling while moving. In this paper, we propose a natural ROI(region of interest) setting and image compression method for effective image sharing among soldiers. We verify the proposed method through prototype system design and implementation of eye gaze detection and ROI-based image compression.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.769-771
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• 2004

요즘 Web-Browsing, 영상 데이터 베이스 그리고 원격 진료와 같은 여러 응용 분야에서는 압축할 이미지내의 사용자의 관심 영역을 다른 영역보다 더 우선적으로 처리할 필요가 있다. 즉, 영상을 전송하는데 있어서 관심영역(ROI ： Region Of Interest)을 먼저 전송하고, 영상 복원 시에도 영상의 전체 영역 중 ROI 영역이 우선적으로 복원하여야 하는 경우가 있다. Maxshift 방법은 JPEG2000 ROI Coding 에서 표준으로 사용하고 있다. 그러나 Maxshift 방법은 단지 하나의 ROI 영역만을 처리 가능하다. 본 논문에서는 기존의 방법을 이용하여 우선 순위를 가지는 Multiple ROI Coding 기법을 제안한다. 제안한 방법에서는 계수값들의 비트 플레인에 대한 스케일링 변수를 이용하여 우선 순위를 가지는 Multiple ROI 부호화가 가능함을 보이고, 저 비트율에서 Maxshift 방법보다 좀 더 우수한 성능을 확인하였다.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1445-1454
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• 2006

To compress a specific part of an image with high quality or to transfer it, JPEG2000 standard offers an ROI(Region-of-Interest) image coding method. What is important in ROI coding is to process relative importance between ROI and background and to process ROI mask. We propose an adaptive ROI coding method supplemented the existing Implicit ROI coding and Modified implicit ROI coding to improve image quality and reduce ROI mask information. The proposed method is an EBCOT-based ROI coding that extracts ROI from the compressed bitstream, and gets the ROI mask information by classifying the codeblocks into 6 patterns. The information includes the pattern type(3bit) and the width(5bit) expressing the boundary between two regions for each codeblock. As a result, the method shows an excellent compression performance in ROI region as well as in the whole region of an image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.324-332
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• 2004

In image communications related to web browsing, image database, and telemedicine, image data processing on the region of interest (ROI) for providing the primary information is needed in the view of saying search time and bandwidth. In this paper, an enhanced algorithm for processing image data that involves multiple ROIs is presented in order to increase PSNR vs. compression ratio performance above the previous JPEG2000 Part1 Maxshift method. Since the wavelet transform enables us to a progressive transmission mechanism, Multiple-ROI coding is possible to compress, transmit, and reconstruct the image data with a better quality than those of non-ROI method while the required transmission bandwidth is kept relatively low.