The algorithm of seamless image mosaic based on A‐KAZE features extraction and reducing the inclination of image

Qu, Zhong; Bu, Wei; Liu, Ling

doi:10.1002/tee.22507

Cited by 13 publications

(4 citation statements)

References 12 publications

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“…These images demonstrate that nonlinear filtering retains more details than linear filtering. A similar conclusion was obtained in Reference [42].…”

Section: Nonlinear Scale Space Constructionsupporting

confidence: 91%

An Image Copy-Move Forgery Detection Scheme Based on A-KAZE and SURF Features

2018

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The popularity of image editing software has made it increasingly easy to alter the content of images. These alterations threaten the authenticity and integrity of images, causing misjudgments and possibly even affecting social stability. The copy-move technique is one of the most commonly used approaches for manipulating images. As a defense, the image forensics technique has become popular for judging whether a picture has been tampered with via copy-move, splicing, or other forgery techniques. In this paper, a scheme based on accelerated-KAZE (A-KAZE) and speeded-up robust features (SURF) is proposed for image copy-move forgery detection (CMFD). It is difficult for most keypoint-based CMFD methods to obtain sufficient points in smooth regions. To remedy this defect, the response thresholds for the A-KAZE and SURF feature detection stages are set to small values in the proposed method. In addition, a new correlation coefficient map is presented, in which the duplicated regions are demarcated, combining filtering and mathematical morphology operations. Numerous experiments are conducted to demonstrate the effectiveness of the proposed method in searching for duplicated regions and its robustness against distortions and post-processing techniques, such as noise addition, rotation, scaling, image blurring, joint photographic expert group (JPEG) compression, and hybrid image manipulation. The experimental results demonstrate that the performance of the proposed scheme is superior to that of other tested CMFD methods.

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“…These images demonstrate that nonlinear filtering retains more details than linear filtering. A similar conclusion was obtained in Reference [42].…”

Section: Nonlinear Scale Space Constructionsupporting

confidence: 91%

An Image Copy-Move Forgery Detection Scheme Based on A-KAZE and SURF Features

2018

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“…Alcantarilla et al [5] proposed an A-KAZE feature extraction method based on nonlinear scale decomposition. In our previous work [6], we proposed an image stitching method based on A-KAZE feature extraction. A-KAZE algorithm can better register images with large affine transformation, and better retain edges and details.…”

Section: Image Registrationmentioning

confidence: 99%

Unordered Image Stitching Based on the Registration Index Table

2022

J. Phys.: Conf. Ser.

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In order to solve the problem of large amount of calculation and time-consuming in the process of unordered image stitching, we propose an image stitching algorithm based on the image registration index table in this paper. Firstly, we construct the matching index sequence based on the similarity of the matching area. Then we search for image matching pairs according to the matching index sequence, carry out image registration and stitch directly, and generate the registration index table. For image stitching, we build a binary tree model assisted by the image registration index table, we need to search for matching pairs and carry out registration and stitching according to the registration index table generated by each layer. Compare to the current research on disordered image stitching, our method significantly reduces the times of feature extraction and matching by at least half, therefore, it greatly improves the efficiency of image stitching.

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“…Even though SIFT has good robustness it has some flaws such as it does not neither preserve object boundaries nor smooth the same level and noise at all scales. An alternative approach namely A-KAZE algorithm [1] overcomes this problem where the multi-resolution fusion algorithm is used to fuse the image in order to achieve a satisfactory seamless image of high resolution.…”

Section: Feature-based Techniquementioning

confidence: 99%

The Feature based Image Stitching Techniques

Kumar¹,

Kumar²,

Prasanth³

et al. 2019

IJRTE

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The photographic images taken from different sources are integrated into one to form a new panoramic image which has high resolution when compared to the original image. Usually, image stitching can be done using any computer software. Image stitching helps us in extracting the actual information from shredded data. The torned paper can be reconstructed by means of image stitching process which is applied in forensic department. Digital maps and satellite photos can be reconstructed through image stitching algorithms which is also known as Image mosics. In recent days, many researchers introduced various algorithms to address the issues in Image stitching technique. Feature based Image stitching technique plays a vital role in most of these algorithms. In feature-based technique, local descriptor is used to compare an image’s feature points with another image’s feature points to predict the feature points for the given pair of image. In this paper different image stitching techniques, comparisons between various features descriptor and the steps involved in Feature extraction in Image stitching method are discussed.

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The algorithm of seamless image mosaic based on A‐KAZE features extraction and reducing the inclination of image

Cited by 13 publications

References 12 publications

An Image Copy-Move Forgery Detection Scheme Based on A-KAZE and SURF Features

An Image Copy-Move Forgery Detection Scheme Based on A-KAZE and SURF Features

Unordered Image Stitching Based on the Registration Index Table

The Feature based Image Stitching Techniques

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