Image Stitching using AKAZE Features

Sharma, Surendra Kumar; Jain, Kamal

doi:10.1007/s12524-020-01163-y

Cited by 31 publications

(18 citation statements)

References 30 publications

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“…AKAZE implements fast explicit diffusion (FED) [23] embedded in a pyramidal framework that enhances the speed of feature detection in nonlinear scale space. Key points are located by finding the extrema of the second-order derivatives of the image over the nonlinear multi-scale pyramid built from the principle of image diffusion [24]. The FED expression is shown in Formula (4):…”

Section: Feature Points Extraction and Matchingmentioning

confidence: 99%

3D Texture Reconstruction of Abdominal Cavity Based on Monocular Vision SLAM for Minimally Invasive Surgery

et al. 2022

Symmetry

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The depth information of abdominal tissue surface and the position of laparoscope are very important for accurate surgical navigation in computer-aided surgery. It is difficult to determine the lesion location by empirically matching the laparoscopic visual field with the preoperative image, which is easy to cause intraoperative errors. Aiming at the complex abdominal environment, this paper constructs an improved monocular simultaneous localization and mapping (SLAM) system model, which can more accurately and truly reflect the abdominal cavity structure and spatial relationship. Firstly, in order to enhance the contrast between blood vessels and background, the contrast limited adaptive histogram equalization (CLAHE) algorithm is introduced to preprocess abdominal images. Secondly, combined with AKAZE algorithm, the Oriented FAST and Rotated BRIEF(ORB) algorithm is improved to extract the features of abdominal image, which improves the accuracy of extracted symmetry feature points pair and uses the RANSAC algorithm to quickly eliminate the majority of mis-matched pairs. The medical bag-of-words model is used to replace the traditional bag-of-words model to facilitate the comparison of similarity between abdominal images, which has stronger similarity calculation ability and reduces the matching time between the current abdominal image frame and the historical abdominal image frame. Finally, Poisson surface reconstruction is used to transform the point cloud into a triangular mesh surface, and the abdominal cavity texture image is superimposed on the 3D surface described by the mesh to generate the abdominal cavity inner wall texture. The surface of the abdominal cavity 3D model is smooth and has a strong sense of reality. The experimental results show that the improved SLAM system increases the registration accuracy of feature points and the densification, and the visual effect of dense point cloud reconstruction is more realistic for Hamlyn dataset. The 3D reconstruction technology creates a realistic model to identify the blood vessels, nerves and other tissues in the patient’s focal area, enabling three-dimensional visualization of the focal area, facilitating the surgeon’s observation and diagnosis, and digital simulation of the surgical operation to optimize the surgical plan.

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Section: Feature Points Extraction and Matchingmentioning

confidence: 99%

3D Texture Reconstruction of Abdominal Cavity Based on Monocular Vision SLAM for Minimally Invasive Surgery

et al. 2022

Symmetry

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“…Each algorithm has its own advantages and disadvantages. AKAZE [20]and KAZE [6]are nonlinear algorithms [33], which cost much time to process image and are not suitable for auto mobile industry production line. BRISK or SIFT or SURF or ORB algorithm [21] is a linear algorithm with fast processing speed.…”

Section: Bshortcoming Of Detecting Local Feature Algorithmsmentioning

confidence: 99%

A Method for Identifying Flaws on Product Surface Based on Spatial Connectivity Domain

et al. 2021

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In this paper, we exploit a method for identifying flaws on product surface based on spatial connectivity domain. A number of algorithms for detecting local features exist that were established to enhance the efficiency and accuracy of identifying interest features, such as AKAZE , BFSIFT , BRIEF , BRISK , ORB , SURF , SIFT and PCA-SIFT algorithm. But the data of flaws on product surface which is similar and consistent with the background intensity became a dilemma to detect the feature of image. In terms of identifying flaws on product surface, the above algorithms are not effective and accurate. Our aim is to enhance the accuracy of detecting the feature of flaws on product surface, so that the product with flaws could be accurately identified in industrial production. Therefore, we propose a method to identify flaws on product surface based on spatial connectivity domain. Compared with some other algorithms, the proposed method is more effective and accurate in detecting the local feature flaws on product surface of auto parts in automotive manufacturing factory.

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“…Herng-Hua Chang et al [ 10 ] improved the Scale Invariant Feature Transform (SIFT) operator, feature slope calculation, feature point grouping, the and outlier removal and transformation were adopted. SK sharma et al [ 11 ] utilized AKAZE to detect feature points, obtained corresponding matching pairs by using K-NN algorithm, and removed the false matched points by MSAC.…”

Section: Introductionmentioning

confidence: 99%

Research on Panoramic Stitching Algorithm of Lateral Cranial Sequence Images in Dental Multifunctional Cone Beam Computed Tomography

Liu

Shen

et al. 2021

Sensors

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In the design of dental multifunctional Cone Beam Computed Tomography, the linear scanning strategy not only saves equipment cost, but also avoids the demand for patients to be repositioned when acquiring lateral cranial sequence images. In order to obtain panoramic images, we propose a local normalized cross-correlation stitching algorithm based on Gaussian Mixture Model. Firstly, the Block-Matching and 3D filtering algorithm is used to remove quantum and impulse noises according to the characteristics of X-ray images; Then, the segmentation of the irrelevant region and the extraction of the region of interest are performed by Gaussian Mixture Model; The locally normalized cross-relation is used to complete the registration with the multi-resolution strategy based on wavelet transform and Particle Swarm Optimization algorithm; Finally, image fusion is achieved by the weighted smoothing fusion algorithm. The experimental results show that the panoramic image obtained by this method has significant performance in both subjective vision and objective quality evaluation and can be applied to preoperative diagnosis of clinical dental deformity and postoperative effect evaluation.

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Image Stitching using AKAZE Features

Cited by 31 publications

References 30 publications

3D Texture Reconstruction of Abdominal Cavity Based on Monocular Vision SLAM for Minimally Invasive Surgery

3D Texture Reconstruction of Abdominal Cavity Based on Monocular Vision SLAM for Minimally Invasive Surgery

A Method for Identifying Flaws on Product Surface Based on Spatial Connectivity Domain

Research on Panoramic Stitching Algorithm of Lateral Cranial Sequence Images in Dental Multifunctional Cone Beam Computed Tomography

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