• Title/Summary/Keyword: image cropping

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Image Watermarking Robust to Geometrical Attacks based on Normalization using Invariant Centroid (불변의 무게중심을 이용한 영상 정규화에 기반한 기하학적 공격에 강인한 워터마킹)

  • 김범수;최재각
    • Journal of KIISE:Information Networking
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    • v.31 no.3
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    • pp.243-251
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    • 2004
  • This paper proposes a digital image watermarking scheme, which is robust to geometrical attacks. The method improves image normalization-based watermarking (INW) technique that doesn't effectively deal with geometrical attacks with cropping. Image normalization is based on the moments of the image, however, in general, geometrical attacks bring the image boundary cropping and the moments are not preserved original ones. Thereafter the normalized images of before and after are not same form, i.e., the synchronization is lost. To solve the cropping problem of INW, Invariant Centroid (IC) is proposed in this paper. IC is a gravity center of a central area on a gray scale image that is invariant although an image is geometrically attacked and the only central area, which has less cropping possibility by geometrical attacks, is used for normalization. Experimental results show that the IC-based method is especially robust to geometrical attack with cropping.

A Survey on Content Aware Image Resizing Methods

  • Garg, Ankit;Negi, Ashish
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.2997-3017
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    • 2020
  • With the advancement in the field of image processing, images are being processed using various image processing algorithms. Nowadays, many efficient content-aware image resizing techniques are being used to safeguard the prominent regions and to generate better results that are visually appealing and pleasing while resizing. Advancements in the new display device with varying screen size demands the development of efficient image resizing algorithm. This paper presents a survey on various image retargeting methods, comparison of image retargeting results based on performance, and also exposes the main challenges in image retargeting such as content preservation of important regions, distortion minimization, and improving the efficiency of image retargeting methods. After reviewing literature from researchers it is suggested that the use of the single operator in image retargeting such as scaling, cropping, seam carving, and warping is not sufficient for obtaining satisfactory results, hence it is essential to combine multiple image retargeting operators. This survey is useful for the researchers interested in content-aware image retargeting.

Impacts of label quality on performance of steel fatigue crack recognition using deep learning-based image segmentation

  • Hsu, Shun-Hsiang;Chang, Ting-Wei;Chang, Chia-Ming
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.207-220
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    • 2022
  • Structural health monitoring (SHM) plays a vital role in the maintenance and operation of constructions. In recent years, autonomous inspection has received considerable attention because conventional monitoring methods are inefficient and expensive to some extent. To develop autonomous inspection, a potential approach of crack identification is needed to locate defects. Therefore, this study exploits two deep learning-based segmentation models, DeepLabv3+ and Mask R-CNN, for crack segmentation because these two segmentation models can outperform other similar models on public datasets. Additionally, impacts of label quality on model performance are explored to obtain an empirical guideline on the preparation of image datasets. The influence of image cropping and label refining are also investigated, and different strategies are applied to the dataset, resulting in six alternated datasets. By conducting experiments with these datasets, the highest mean Intersection-over-Union (mIoU), 75%, is achieved by Mask R-CNN. The rise in the percentage of annotations by image cropping improves model performance while the label refining has opposite effects on the two models. As the label refining results in fewer error annotations of cracks, this modification enhances the performance of DeepLabv3+. Instead, the performance of Mask R-CNN decreases because fragmented annotations may mistake an instance as multiple instances. To sum up, both DeepLabv3+ and Mask R-CNN are capable of crack identification, and an empirical guideline on the data preparation is presented to strengthen identification successfulness via image cropping and label refining.

A Study on the Preparation Method of Fruit Cropping Distribution Map using Satellite Images and GIS (위성영상과 GIS를 이용한 과수재배 분포도 작성 기법에 관한 연구)

  • Jo, Myung-Hee;Bu, Ki-Dong;Lee, Jung-Hyoup;Lee, Kwang-Jae
    • Journal of the Korean Association of Geographic Information Studies
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    • v.3 no.4
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    • pp.73-86
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    • 2000
  • This study focused on extracting an efficient method in the fruit cropping distribution mapping with various classification methods using multi-temporal satellite images and Geographic Information Systems(GIS). For this study, multi-temporal Landsat TM images, in observation data and existing fruit cropping area statistics were used to compare and analyze the properties of fruit cropping and seasonal distribution per classification method. As a result, this study concludes that Maximum Likelihood Method with earlier autumn satellite image was most efficient for the fruit cropping mapping using Landsat TM image. In addition, it was clarified that cropping area per administrative boundary was prepared and distribution pattern was identified efficiently using GIS spatial analysis.

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Log-Polar Image Watermarking based on Invariant Centroid as Template (불변의 무게중심을 템플릿으로 이용한 대수-극 좌표계 영상 워터마킹 기법)

  • 김범수;유광훈;김우섭;곽동민;송영철;최재각;박길흠
    • Journal of KIISE:Computing Practices and Letters
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    • v.9 no.3
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    • pp.341-351
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    • 2003
  • Digital image watermarking is the method that can protect the copyright of the image by embedding copyright information, which is called watermark. Watermarking must have robustness to intentional or unintentional data changing, called attack. The conventional watermarking schemes are robust to waveform attacks such as image compression, filtering etc. However, they are vulnerable to geometrical attacks such as rotation, scaling, translation, and cropping. Accordingly, this paper proposes new watermarking scheme that is robust to geometrical attacks by using invariant centroid. Invariant centroid is the gravity center of a central area in a gray scale image that remains unchanged even when the image is attacked by RST including cropping and proposed scheme uses invariant centroids of original and inverted image as the template. To make geometrically invariant domain, template and angle compensated Log -Polar Map(LPM) is used. Then Discrete Cosine Transform(DCT) is performed and the watermark is embedded into the DCT coefficients. Futhermore, to prevent a watermarked image from degrading due to interpolation during coordinate system conversion, only the image of the watermark signal is extracted and added to the original image. Experimental results show that the proposed scheme is especially robust to RST attacks including cropping.

Fast image stitching method for handling dynamic object problems in Panoramic Images

  • Abdukholikov, Murodjon;Whangbo, Taegkeun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.11
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    • pp.5419-5435
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    • 2017
  • The construction of panoramic images on smartphones and low-powered devices is a challenging task. In this paper, we propose a new approach for smoothly stitching images on mobile phones in the presence of moving objects in the scene. Our main contributions include handling moving object problems, reducing processing time, and generating rectangular panoramic images. First, unique and robust feature points are extracted using fast ORB method and a feature matching technique is applied to match the extracted feature points. After obtaining good matched feature points, we employ the non-deterministic RANSAC algorithm to discard wrong matches, and the hommography transformation matrix parameters are estimated with the algorithm. Afterward, we determine precise overlap regions of neighboring images and calculate their absolute differences. Then, thresholding operation and noise removal filtering are applied to create a mask of possible moving object regions. Sequentially, an optimal seam is estimated using dynamic programming algorithm, and a combination of linear blending with the mask information is applied to avoid seam transition and ghosting artifacts. Finally, image-cropping operation is utilized to obtain a rectangular boundary image from the stitched image. Experiments demonstrate that our method is able to produce panoramic images quickly despite the existence of moving objects.

3D Face Image Watermarking using Wavelet Transform (웨이브렛 변환을 이용한 3차원 얼굴영상 워터마킹)

  • 이정환;박세훈;이시웅
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.10a
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    • pp.691-694
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    • 2003
  • This paper proposes an 3D face image watermarking method based on discrete wavelet transform(DWT). First, 3D face image are transformed by DWT and inserted gaussian watermark into frequency domain. To increase the robustness and perceptual invisibility of watermark, the proposed algorithm is combined with the characteristics of 3D face image and human visual system. The proposed method is invisible and blind watermarking which the original image is not required. Simulation results show that the proposed method is robust to the general attack such as JPEG compression, enhancement, noise, cropping, and filtering etc.

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Digital Image Watermarking based on Wavelet Transform and Spatial (웨이브렛 변환 및 공간지각특성을 이용한 디지털영상 워터마킹)

  • Bae, Mi-Young;Lee, Jeong-Hwan;Kim, Yun-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.1
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    • pp.1165-1168
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    • 2005
  • This paper proposes an digital image watermarking method based on discrete wavelet transform(DWT) and spatial perceptual properties of human visula system. first, an digital image is transformed by DWT and inserted gaussian watermark into the frequency domain. To increase the robustness and perceptual invisibility of watermark, the proposed algorithm is combined with the characteristics of digital image and human visual system. The proposed method is invisible and blind watermarking which the original image is not required to detect watermarks. Simulation results show that the proposed method is robust to the general attack such as JPEG compression, enhancement, noise, cropping, and filtering etc.

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Auto Correction Technique of Photography Composition Using ROI Extraction Method (ROI 추출을 통한 사진 구도 자동 보정 기법)

  • Ha, Ho-Saeng;Park, Dae-Hyun;Kim, Yoon
    • Journal of Information Technology and Architecture
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    • v.10 no.1
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    • pp.113-122
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    • 2013
  • In this paper, we propose the method that automatically corrects the composition of a picture stylishly as well as reliably by cropping pictures based on the Rule of Thirds. The region of interest (ROI) is extracted from a picture by applying the Saliency Map and the Image Segmentation technology, the composition of the photo is amended based on this area to satisfy the Rule of Thirds. In addition, since the face region of the person is added to ROI by the Face Detection technique and the composition is amended by the various scenario according to ROI, the little more natural picture is acquired. The experimental result shows that the photo of the corrected composition was naturally amended compared with the original photo.

Image Watermarking using holographic watermark (홀로그래픽 watermark를 이용한 영상 watermarking)

  • 김규태;김수길;고명숙;김종원;최종욱
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2003.11a
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    • pp.175-179
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    • 2003
  • We propose a new watermarking scheme that can be used to embed multiple bits and also resilient to JPEG compression and geometrical transforms such as scaling, rotation, and cropping based on holographic watermark that allows multiple watermark recovery without original content(cover image).

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