TOWARDS PRACTICAL SELF-EMBEDDING FOR JPEG-COMPRESSED DIGITAL IMAGES

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Engineering

TOWARDS PRACTICAL SELF-EMBEDDING FOR
JPEG-COMPRESSED DIGITAL IMAGES
ABSTRACT
This paper deals with the design of a practical self-recovery mechanism for lossy
compressed JPEG images. We extend a recently proposed model of the content reconstruction
problem based on digital fountain codes to take into account the impact of emerging watermark
extraction and block classification errors. In contrast to existing methods, our scheme guarantees
a high and stable level of reconstruction quality. Instead of introducing reconstruction artifacts,
emerging watermark extraction errors penalize the achievable tampering rates. We introduce new
mechanisms that allow for handling high-resolution and color images efficiently. In order to
analyze the behavior of our scheme, we derive an improved model to calculate the reconstruction
success probability. We introduce a new hybrid mechanism for spreading the reference
information over the entire image, which allows to find a good balance between the achievable
tampering rates and the computational complexity. Such an approach reduced the watermark
embedding time from the order of several minutes to the order of single seconds, even on mobile
devices.

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Manga is one of popular item in Japan and also in the rest of the world. Hundreds of manga book is printed everyday in Japan, and some of printed manga book is digitized into web content for reading comic through the internet. People then make translation of Japanese language in manga into other language to share enjoy of reading manga for non Japanese reader. However, people make translation of the text on printed comic book (they call it scanlation) in manually because there is no automatic method for translate comic text image into any other language. The challenge in extracting Japanese character in manga is how to detect comic balloon and extract text in vertical direction as Japanese classic writing direction is top down and right to left. Several research projects [1-4] proposed method for text extraction from images but not specific for extraction from comic image. There are two base methods for text extraction, using region based method and texture based method. In [5], propose the concept of automatic mobile content conversion using semantic image analysis that include comic text extraction, but this paper did not explain the details for text extraction. Also, Yamada [6] proposed method for comic image decomposition for reading comic on mobile phone that including comic text extraction but not details on comic text extraction. The conventional method assuming extraction process in offline way and using scanned comic image. In the internet and mobility era, we need advance method for extraction text in online way and automatically

End-to-end learned image and video codecs, based on auto-encoder architecture, adapt naturally to image resolution, thanks to their convolutional aspect. However, while coding high resolution images, these codecs face hardware problems such as memory saturation. This paper proposes a patch-based image coding solution based on an end-to-end learned model, which aims to remedy to the hardware limitation while maintaining the same quality as full resolution image coding. Our method consists in coding overlapping patches of the image and reconstructing them into a decoded image using a weighting function. This approach manages to be on par with the performance of full resolution image coding using an endto-end learned model, and even slightly outperforms it, while being adaptable to different memory sizes. Moreover, this work undertakes a full study on the effect of the patch size on this solution’s performance, and consequently determines the best patch resolution in terms of coding time and coding efficiency. Finally, the method introduced in this work is also compatible with any learned codec based on a conv/deconvolutional autoencoder architecture without having to retrain the model.

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A foggy environment may cause digitally captured images to appear blurry, dim, or low in contrast. This will impact computer vision systems that rely on image information. With the need for real-time image information, such as a plate number recognition system, a simple yet effective image enhancement algorithm using a hardware implementation is very much needed to fulfil the need. To improve images that suffer from low exposure and hazy, the hardware implementations are usually based on complex algorithms. Hence, the aim of this paper is to propose a less complex enhancement algorithm for hardware implementation that is able to improve the quality of such images. The proposed method simply combines brightness and contrast manipulation to enhance the image. In order to see the performance of the proposed method, a total of 100 vehicle registration number images were collected, enhanced, and evaluated. The evaluation results were compared to two other enhancement methods quantitatively and qualitatively. Quantitative evaluation is done by evaluating the output image using peak signal-to-noise ratio and mean-square error evaluation metrics, while a survey is done to evaluate the output image qualitatively. Based on the quantitative evaluation results, our proposed method outperforms the other two enhancement methods.

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学校原件一模一样【微信：741003700 】《(ANU毕业证书)澳洲国立大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。本公司拥有海外各大学样板无数，能完美还原。 1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700 【主营项目】一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！二.真实使馆公证(即留学回国人员证明,不成功不收费) 三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度) 如果您处于以下几种情况： ◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】 ◇面对父母的压力，希望尽快拿到； ◇不清楚认证流程以及材料该如何准备； ◇回国时间很长，忘记办理； ◇回国马上就要找工作，办给用人单位看； ◇企事业单位必须要求办理的 ◇需要报考公务员、购买免税车、落转户口 ◇申请留学生创业基金留信网认证的作用: 1:该专业认证可证明留学生真实身份 2:同时对留学生所学专业登记给予评定 3:国家专业人才认证中心颁发入库证书 4:这个认证书并且可以归档倒地方 5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息 6:个人职称评审加20分 7:个人信誉贷款加10分 8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才

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Democratizing Fuzzing at Scale by Abhishek Arya

abh.arya

Presented at NUS: Fuzzing and Software Security Summer School 2024 This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.

Cosmetic shop management system project report.pdf

Kamal Acharya

Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry. Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks. Data file handling has been effectively used in the program. The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.

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在线办理(ANU毕业证书)澳洲国立大学毕业证录取通知书一模一样

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Democratizing Fuzzing at Scale by Abhishek Arya

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TOWARDS PRACTICAL SELF-EMBEDDING FOR JPEG-COMPRESSED DIGITAL IMAGES

1. TOWARDS PRACTICAL SELF-EMBEDDING FOR JPEG-COMPRESSED DIGITAL IMAGES ABSTRACT This paper deals with the design of a practical self-recovery mechanism for lossy compressed JPEG images. We extend a recently proposed model of the content reconstruction problem based on digital fountain codes to take into account the impact of emerging watermark extraction and block classification errors. In contrast to existing methods, our scheme guarantees a high and stable level of reconstruction quality. Instead of introducing reconstruction artifacts, emerging watermark extraction errors penalize the achievable tampering rates. We introduce new mechanisms that allow for handling high-resolution and color images efficiently. In order to analyze the behavior of our scheme, we derive an improved model to calculate the reconstruction success probability. We introduce a new hybrid mechanism for spreading the reference information over the entire image, which allows to find a good balance between the achievable tampering rates and the computational complexity. Such an approach reduced the watermark embedding time from the order of several minutes to the order of single seconds, even on mobile devices.

TOWARDS PRACTICAL SELF-EMBEDDING FOR JPEG-COMPRESSED DIGITAL IMAGES

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TOWARDS PRACTICAL SELF-EMBEDDING FOR JPEG-COMPRESSED DIGITAL IMAGES