Computing Parallel Speeded-Up Robust Features (P-SURF) via POSIX Threads

2009 ◽  
pp. 287-296 ◽  
Author(s):  
Nan Zhang
Keyword(s):  
Posix Threads ◽  
Speeded Up Robust Features

scholarly journals Research on Remote Sensing Image Matching with Special Texture Background

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1380
Author(s):  
Sen Wang ◽  
Xiaoming Sun ◽  
Pengfei Liu ◽  
Kaige Xu ◽  
Weifeng Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Image ◽  
Geometric Distortion ◽  
Reference Image ◽  
Remote Sensing Images ◽  
Scale Invariant ◽  
Sift Algorithm ◽  
Speeded Up Robust Features ◽  
Adaptive Quantization ◽  
Texture Background

The purpose of image registration is to find the symmetry between the reference image and the image to be registered. In order to improve the registration effect of unmanned aerial vehicle (UAV) remote sensing imagery with a special texture background, this paper proposes an improved scale-invariant feature transform (SIFT) algorithm by combining image color and exposure information based on adaptive quantization strategy (AQCE-SIFT). By using the color and exposure information of the image, this method can enhance the contrast between the textures of the image with a special texture background, which allows easier feature extraction. The algorithm descriptor was constructed through an adaptive quantization strategy, so that remote sensing images with large geometric distortion or affine changes have a higher correct matching rate during registration. The experimental results showed that the AQCE-SIFT algorithm proposed in this paper was more reasonable in the distribution of the extracted feature points compared with the traditional SIFT algorithm. In the case of 0 degree, 30 degree, and 60 degree image geometric distortion, when the remote sensing image had a texture scarcity region, the number of matching points increased by 21.3%, 45.5%, and 28.6%, respectively and the correct matching rate increased by 0%, 6.0%, and 52.4%, respectively. When the remote sensing image had a large number of similar repetitive regions of texture, the number of matching points increased by 30.4%, 30.9%, and −11.1%, respectively and the correct matching rate increased by 1.2%, 0.8%, and 20.8% respectively. When processing remote sensing images with special texture backgrounds, the AQCE-SIFT algorithm also has more advantages than the existing common algorithms such as color SIFT (CSIFT), gradient location and orientation histogram (GLOH), and speeded-up robust features (SURF) in searching for the symmetry of features between images.

POSIX Threads (Pthreads)

2011 ◽  
pp. 1592-1593
Author(s):  
Bruce Leasure ◽  
David J. Kuck ◽  
Sergei Gorlatch ◽  
Murray Cole ◽  
Gregory R. Watson ◽  
...  
Keyword(s):  
Posix Threads

scholarly journals Fast Image Registration for Spacecraft Autonomous Navigation Using Natural Landmarks

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Yun-Hua Wu ◽  
Lin-Lin Ge ◽  
Feng Wang ◽  
Bing Hua ◽  
Zhi-Ming Chen ◽  
...  
Keyword(s):  
Image Registration ◽  
Autonomous Navigation ◽  
Computational Cost ◽  
Segmentation Algorithm ◽  
Speeded Up Robust Features ◽  
Speed Up ◽  
Random Sample Consensus ◽  
Invariant Properties ◽  
Low Computational Cost ◽  
Ransac Algorithm

In order to satisfy the real-time requirement of spacecraft autonomous navigation using natural landmarks, a novel algorithm called CSA-SURF (chessboard segmentation algorithm and speeded up robust features) is proposed to improve the speed without loss of repeatability performance of image registration progress. It is a combination of chessboard segmentation algorithm and SURF. Here, SURF is used to extract the features from satellite images because of its scale- and rotation-invariant properties and low computational cost. CSA is based on image segmentation technology, aiming to find representative blocks, which will be allocated to different tasks to speed up the image registration progress. To illustrate the advantages of the proposed algorithm, PCA-SURF, which is the combination of principle component analysis and SURF, is also analyzed in this paper for comparison. Furthermore, random sample consensus (RANSAC) algorithm is applied to eliminate the false matches for further accuracy improvement. The simulation results show that the proposed strategy obtains good results, especially in scaling and rotation variation. Besides, CSA-SURF decreased 50% of the time in extraction and 90% of the time in matching without losing the repeatability performance by comparing with SURF algorithm. The proposed method has been demonstrated as an alternative way for image registration of spacecraft autonomous navigation using natural landmarks.

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

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 706 ◽  
Author(s):  
Chengyou Wang ◽  
Zhi Zhang ◽  
Xiao Zhou
Keyword(s):  
Feature Detection ◽  
Joint Photographic Expert Group ◽  
Social Stability ◽  
Forgery Detection ◽  
Detection Scheme ◽  
Speeded Up Robust Features ◽  
Image Blurring ◽  
Surf Features ◽  
Copy Move Forgery Detection ◽  
Processing Techniques

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.

scholarly journals PENERAPAN ALGORITMA SURF PENDETEKSI OBJEK PADA AUGMENTED REALITY BERBASIS ANDROID

2020 ◽  
Vol 6 (2) ◽  
pp. 240-249
Author(s):  
Ari Amir Alkodri Ari
Keyword(s):  
Augmented Reality ◽  
Object Oriented ◽  
Object Oriented Programming ◽  
Speeded Up Robust Features

             Untuk penerapan konsep yang efektif dan efisien dalam pembelajaran menggunakan teknologi augmented reality yang interaktif. Pembelajaran multimedia merupakan bentuk pembelajaran secara interaktif. Pembelajaran dapat dilakukan dikelas maupun dalam bentuk tugas dirumah. Dampak dari pembelajaran interaktif ini sangat mempengaruhi kualitas pemahaman bagi pengguna. Berdasarkan pengujian dari teknologi augmented reality, penelitian, analisis dan analisis desain antarmuka interaktif, proses dan prinsip dilakukan melalui interaksi manusia dan komputer serta pengalaman pengguna. Metode desain antarmuka menggunakan metode Object Oriented Programming dan algoritma Speeded Up Robust Features. Hasil penelitian menunjukkan bahwa augmented reality interaktif dapat memberikan metode baru dalam proses pembelajaran dan memperbarui konten pembelajaran di kelas. Singkatnya, metode ini meningkatkan partisipasi dan antusiasme siswa, dan meningkatkan efektivitas pembelajaran.

scholarly journals Programowanie wielowątkowe w językach strukturalnych i obiektowych

2019 ◽  
Vol 10 ◽  
pp. 49-53
Author(s):  
Mateusz Wiśniewski
Keyword(s):  
Posix Threads

W artykule przedstawiono sposoby programowania wielowątkowego w wybranych językach programowania takich jak: C podejście strukturalne oraz obiektowe C++ przy użyciu bibliotek Posix Threads dla języka C oraz bibliotekę Boost dla języka C++. Opisano również charakterystykę wybranych bibliotek. Przedstawiono przykładowe rozwiązania typowych problemów programistycznych wykorzystujących wątki. Starano odpowiedzieć na pytanie czym kierować się przy wyborze języka do nauki programowania wielowątkowego oraz programowania w ogólnym tego słowa znaczeniu.

scholarly journals Comparative evaluation of three image analysis methods for angular displacement measurement in a MEMS microgripper prototype: a preliminary study

ACTA IMEKO ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 119
Author(s):  
Federica Vurchio ◽  
Giorgia Fiori ◽  
Andrea Scorza ◽  
Salvatore Andrea Sciuto
Keyword(s):  
Image Analysis ◽  
Angular Displacement ◽  
Functional Characterization ◽  
Displacement Measurement ◽  
Mems Devices ◽  
Speeded Up Robust Features ◽  
Relevant Today ◽  
Measurement Results ◽  
Preliminary Study

<p class="Abstract"><span lang="EN-US">The functional characterization of MEMS devices is relevant today since it aims at verifying the behavior of these devices, as well as improving their design. In this regard, this study focused on the functional characterization of a MEMS microgripper prototype suitable in biomedical applications: the measurement of the angular displacement of the microgripper comb-drive is carried out by means of two novel automatic procedures, based on an image analysis method, SURF-based (Angular Displacement Measurement based on Speeded Up Robust Features, ADM<sub>SURF</sub>) and FFT-based (Angular Displacement Measurement based on Fast Fourier Transform, ADM<sub>FFT</sub>) method, respectively. Moreover, the measurement results are compared with a Semi-Automatic Method (SAM), to evaluate which of them is the most suitable for the functional characterization of the device. The curve fitting of the outcomes from SAM and ADM<sub>SURF</sub>, showed a quadratic trend in agreement with the analytical model. Moreover, the ADM<sub>SURF</sub> measurements below 1° are affected by an uncertainty of about 0.08° for voltages less than 14 V, confirming its suitability for microgripper characterization. It was also evaluated that the ADM<sub>FFT</sub> is more suitable for measurement of rotations greater than 1° (up to 30°), with a measurement uncertainty of 0.02°, at 95% of confidence level.</span></p>

scholarly journals Image Detection System Using Image Processing

2021 ◽  
Vol 9 (VI) ◽  
pp. 5356-5362
Author(s):  
Mohini Gawande
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Detection System ◽  
Estimation Method ◽  
Scale Invariant ◽  
Matrix Estimation ◽  
Speeded Up Robust Features ◽  
Invariant Features ◽  
Marketing Analysis ◽  
New Strategies

The increasing popularity of Social Networks makes change the way people interact. These interactions produce a huge amount of data and it opens the door to new strategies and marketing analysis. According to Instagram and Tumblr, an average of 80 and 59 million photos respectively are published every day, and those pictures contain several implicit or explicit brand logos. Image recognition is one of the most important fields of image processing and computer vision. The CNNs are a very effective class of neural networks that is highly effective at the task of image classifying, object detection and other computer vision problems.in recent years, several scale- invariant features have been proposed in literature, this paper analyzes the usage of Speeded Up Robust Features (SURF) as local descriptors, and as we will see, they are not only scale-invariant features, but they also offer the advantage of being computed very efficiently. Furthermore, a fundamental matrix estimation method based on the RANSAC is applied.

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