Image Stitching Based on Improved SURF Algorithm

Qi, Jinxian; Li, Gongfa; Ju, Zhaojie; Chen, Disi; Du, Jiang; Tao, Bo; Jiang, Guozhang; Sun, Ying

doi:10.1007/978-3-030-27541-9_42

Cited by 8 publications

(4 citation statements)

References 17 publications

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“…The weighting box filters in SURF are utilized and represented as the second order Gaussian partial derivative approximation in x-direction, y-direction, and xy-direction. As shown in Figure-2, the white lobes represent the negative coefficients, black lobes the positive coefficients, and grey lobs the zero values [12].…”

Section: Detection Of Interest Pointsmentioning

confidence: 99%

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Ultrasound Images Registration Based on Optimal Feature Descriptor Using Speeded Up Robust Feature

Joey

Alsudani

Esmaile³

2020

eijs

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Image registration plays a significant role in the medical image processing field. This paper proposes a development on the accuracy and performance of the Speeded-Up Robust Surf (SURF) algorithm to create Extended Field of View (EFoV) Ultrasound (US) images through applying different matching measures. These measures include Euclidean distance, cityblock distance, variation, and correlation in the matching stage that was built in the SURF algorithm. The US image registration (fusion) was implemented depending on the control points obtained from the used matching measures. The matched points with higher frequency algorithm were proposed in this work to perform and enhance the EFoV for the US images, since the maximum accurate matching points would have been selected. The resulted fused images of these applied methods were evaluated subjectively and objectively. The objective assessment was conducted by calculating the execution time, peak signal to noise ratio (PSNR), and signal to noise ratio (SNR) of the registered images and the reference image which was fused manually by a physician. The results showed that the cityblock distance has the best result since it has the highest PSNR and SNR in addition to the lowest execution time.

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Section: Detection Of Interest Pointsmentioning

confidence: 99%

“…). Then, a vector which is a four-dimension (4D) will be generated in each sub-region after calculating the eigenvector normalization [12]:…”

Section: Description Of Interest Pointsmentioning

confidence: 99%

Ultrasound Images Registration Based on Optimal Feature Descriptor Using Speeded Up Robust Feature

Joey

Alsudani

Esmaile³

2020

eijs

View full text Add to dashboard Cite

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“…To use this technique for panorama generation, the positioning of cameras must be set carefully with sufficient overlapping regions between adjacent cameras. The images are then stitched together using feature-based stitching algorithms [8,9]. The third technique creates panoramas using an embedded panoramic generation system [10,11] with resource-constrained devices such as mobile cameras or low-power, hand-held visual sensors.…”

Section: Introductionmentioning

confidence: 99%

Automatic 360° Mono-Stereo Panorama Generation Using a Cost-Effective Multi-Camera System

Ullah

Zia

Kim³

et al. 2020

Sensors

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In recent years, 360° videos have gained the attention of researchers due to their versatility and applications in real-world problems. Also, easy access to different visual sensor kits and easily deployable image acquisition devices have played a vital role in the growth of interest in this area by the research community. Recently, several 360° panorama generation systems have demonstrated reasonable quality generated panoramas. However, these systems are equipped with expensive image sensor networks where multiple cameras are mounted in a circular rig with specific overlapping gaps. In this paper, we propose an economical 360° panorama generation system that generates both mono and stereo panoramas. For mono panorama generation, we present a drone-mounted image acquisition sensor kit that consists of six cameras placed in a circular fashion with optimal overlapping gap. The hardware of our proposed image acquisition system is configured in such way that no user input is required to stitch multiple images. For stereo panorama generation, we propose a lightweight, cost-effective visual sensor kit that uses only three cameras to cover 360° of the surroundings. We also developed stitching software that generates both mono and stereo panoramas using a single image stitching pipeline where the panorama generated by our proposed system is automatically straightened without visible seams. Furthermore, we compared our proposed system with existing mono and stereo contents generation systems in both qualitative and quantitative perspectives, and the comparative measurements obtained verified the effectiveness of our system compared to existing mono and stereo generation systems.

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“…Image local patch descriptor has a wide variety of applications in object recognition, such as plant species [1], blood cell [2], and fingerprint [3]. Moreover, the image retrieval [4], 3D scene reconstruction [5], and panoramic stitching [6] problems also utilize the local patch descriptors. The local features are employed to track [7], localize [8] objects in the image.…”

Section: Introductionmentioning

confidence: 99%

Image Local Features Description Through Polynomial Approximation

et al. 2019

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This work introduces a novel local patch descriptor that remains invariant under varying conditions of orientation, viewpoint, scale, and illumination. The proposed descriptor incorporate polynomials of various degrees to approximate the local patch within the image. Before feature detection and approximation, the image micro-texture is eliminated through a guided image filter with the potential to preserve the edges of the objects. The rotation invariance is achieved by aligning the local patch around the Harris corner through the dominant orientation shift algorithm. Weighted threshold histogram equalization (WTHE) is employed to make the descriptor insensitive to illumination changes. The correlation coefficient is used instead of Euclidean distance to improve the matching accuracy. The proposed descriptor has been extensively evaluated on the Oxford's affine covariant regions dataset, and absolute and transition tilt dataset. The experimental results show that our proposed descriptor can categorize the feature with more distinctiveness in comparison to state-of-the-art descriptors. INDEX TERMS Covariant, descriptor, handcrafted feature, patch, textures.

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Image Stitching Based on Improved SURF Algorithm

Cited by 8 publications

References 17 publications

Ultrasound Images Registration Based on Optimal Feature Descriptor Using Speeded Up Robust Feature

Ultrasound Images Registration Based on Optimal Feature Descriptor Using Speeded Up Robust Feature

Automatic 360° Mono-Stereo Panorama Generation Using a Cost-Effective Multi-Camera System

Image Local Features Description Through Polynomial Approximation

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