A New Algorithm of Image Matching Combining Sift and Shape Context

2014 ◽  
Vol 644-650 ◽  
pp. 4307-4313
Author(s):  
Yan Lu Xu ◽  
Yan Ma ◽  
Shun Bao Li ◽  
Ning Li Zhang ◽  
Xiang Fen Zhang ◽  
...  
Keyword(s):  
Image Matching ◽  
Experimental Results ◽  
Feature Points ◽  
Shape Context ◽  
Matching Accuracy ◽  
Conventional Methods ◽  
Distance Formula

This paper presents a new algorithm of image matching via combining sift and shape context for improving image matching accuracy. A joint descriptor is applied to describe feature points. The initial matching is obtained by a proposed distance formula. Furthermore, PLS is introduced to eliminate mismatched points. Experimental results demonstrate the proposed algorithm can achieve better performance compared to conventional methods.

An Improved Algorithm on Adaptive KLT Vision Tracking

2013 ◽  
Vol 631-632 ◽  
pp. 1270-1275
Author(s):  
Yuan Min Liu ◽  
Lian Fang Tian
Keyword(s):  
State Of The Art ◽  
Tracking System ◽  
Tracking Algorithm ◽  
Experimental Results ◽  
Feature Points ◽  
Backward Error ◽  
Tracking Method ◽  
Adaptive Tracking ◽  
Conventional Methods ◽  
Measurement Validity

In view of the shortage of the KLT (Kanade-Lucas-Tomasi) tracking algorithm, an improved adaptive tracking method based on KLT is proposed in this paper, in which a kind of filtering mechanism is applied to decrease the effects of noise and illumination on tracking system. In order to eliminate the error of tracking, the strategies based on forward-backward error and measurement validity are utilized properly. However, because the approach to forward-backward error makes the feature points reduce, which leads to tracking failure especially when the shapes of object change, a method for appending the feature points is introduced. Experimental results indicate that the method presented in this paper is state of the art robustness in our comparison with related work and demonstrate improved generalization over the conventional methods.

An Adaptive KLT Algorithm for Hand Gesture Tracking

2013 ◽  
Vol 706-708 ◽  
pp. 623-628
Author(s):  
Huang Xin
Keyword(s):  
Human Computer Interaction ◽  
State Of The Art ◽  
Tracking System ◽  
Adaptive Method ◽  
Experimental Results ◽  
Hand Gesture ◽  
Feature Points ◽  
Tracking Algorithms ◽  
Gesture Tracking ◽  
Conventional Methods

With the development of human-computer interaction technology, hand gesture is widely investigated recently for its natural and convenient properties. In view of the disadvantage of the existing tracking algorithms for the hand gesture, a novel adaptive method based on KLT is proposed in this paper, in which a kind of filtering mechanism is applied to decrease the effects of noise and illumination on tracking system. In order to eliminate the error of tracking, the strategy based on confidence is utilized properly. However, because the hand is non-rigid, its shape often changes, which easily leads to tracking failure for the reduction of features. In order to solve the problem, a method for appending the feature points is introduced. Experimental results indicate that the method presented in this paper is state of the art robustness in our comparison with related work and demonstrate improved generalization over the conventional methods.

scholarly journals A fast RFID image matching algorithm for multi-tag identification and distribution optimization

2021 ◽  
Vol 15 ◽  
pp. 174830262110126
Author(s):  
Ke Zhang ◽  
Xiaolei Yu ◽  
Lin Li ◽  
Zhenlu Liu ◽  
Shanhao Zhou ◽  
...  
Keyword(s):  
Real Time ◽  
Image Matching ◽  
Positioning System ◽  
Feature Points ◽  
High Complexity ◽  
Matching Accuracy ◽  
Tag Identification ◽  
Positioning Accuracy ◽  
Precise Positioning ◽  
Matching Algorithm

We propose an improved image matching algorithm that combines the minimum feature value algorithm to extract feature points and the direction gradient histogram to calculate the description vector. This algorithm is oriented to RFID multi-tag identification and distribution optimization in the actual scenario, and the traditional SURF algorithm has the problems of low matching accuracy and high complexity in multi-tag matching. This algorithm effectively improves the positioning accuracy of the RFID multi-tag positioning system. The experimental results show that the matching success rate of the improved algorithm in this paper is 87.4%, which is 50% higher than the SURF algorithm. Not only the matching accuracy is greatly improved, but the running speed is also increased by 48%. The algorithm in this paper has high matching accuracy and real-time performance.It provides an effective way for RFID multi-tag real-time fast matching and precise positioning.

scholarly journals A Multi-Resolution Approach to GAN-Based Speech Enhancement

2021 ◽  
Vol 11 (2) ◽  
pp. 721
Author(s):  
Hyung Yong Kim ◽  
Ji Won Yoon ◽  
Sung Jun Cheon ◽  
Woo Hyun Kang ◽  
Nam Soo Kim
Keyword(s):  
Speech Enhancement ◽  
Optimal Solution ◽  
Experimental Results ◽  
Generative Adversarial Networks ◽  
The Real ◽  
Multi Scale ◽  
Adversarial Networks ◽  
Speech Characteristics ◽  
Conventional Methods ◽  
Convex Property

Recently, generative adversarial networks (GANs) have been successfully applied to speech enhancement. However, there still remain two issues that need to be addressed: (1) GAN-based training is typically unstable due to its non-convex property, and (2) most of the conventional methods do not fully take advantage of the speech characteristics, which could result in a sub-optimal solution. In order to deal with these problems, we propose a progressive generator that can handle the speech in a multi-resolution fashion. Additionally, we propose a multi-scale discriminator that discriminates the real and generated speech at various sampling rates to stabilize GAN training. The proposed structure was compared with the conventional GAN-based speech enhancement algorithms using the VoiceBank-DEMAND dataset. Experimental results showed that the proposed approach can make the training faster and more stable, which improves the performance on various metrics for speech enhancement.

An Image Matching Algorithm Based on SIFT and Invariability of Feature Points Set

2011 ◽  
Vol 121-126 ◽  
pp. 701-704
Author(s):  
Xue Tong Wang ◽  
Yao Xu ◽  
Feng Gao ◽  
Jing Yi Bai
Keyword(s):  
Image Matching ◽  
Singular Value ◽  
Feature Points ◽  
Matching Algorithm ◽  
Candidate Feature

Feature points can be used to match images. Candidate feature points are extracted through SIFT firstly. Then feature points are selected from candidate points through singular value decomposing. Distance between feature points sets is computed According to theory of invariability of feature points set, images are matched if the distance is less than a threshold. Experiment showed that this algorithm is available.

scholarly journals Handwritten tifinagh character recognition using simple geometric shapes and graphs

2019 ◽  
Vol 13 (2) ◽  
pp. 598
Author(s):  
Youssef Ouadid ◽  
Abderrahmane Elbalaoui ◽  
Mehdi Boutaounte ◽  
Mohamed Fakir ◽  
Brahim Minaoui
Keyword(s):  
Character Recognition ◽  
Graph Matching ◽  
Recognition Rate ◽  
Recognition System ◽  
Features Extraction ◽  
Experimental Results ◽  
Feature Points ◽  
Matching Method ◽  
Extraction Algorithm ◽  
Novel Algorithm

<p>In this paper, a graph based handwritten Tifinagh character recognition system is presented. In preprocessing Zhang Suen algorithm is enhanced. In features extraction, a novel key point extraction algorithm is presented. Images are then represented by adjacency matrices defining graphs where nodes represent feature points extracted by a novel algorithm. These graphs are classified using a graph matching method. Experimental results are obtained using two databases to test the effectiveness. The system shows good results in terms of recognition rate.</p>

scholarly journals Charuco Board-Based Omnidirectional Camera Calibration Method

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 421 ◽  
Author(s):  
Gwon An ◽  
Siyeong Lee ◽  
Min-Woo Seo ◽  
Kugjin Yun ◽  
Won-Sik Cheong ◽  
...  
Keyword(s):  
Camera Calibration ◽  
Mean Absolute Error ◽  
Three Dimensional ◽  
Absolute Error ◽  
Calibration Method ◽  
Feature Points ◽  
Omnidirectional Camera ◽  
Reprojection Error ◽  
Conventional Methods ◽  
Better Than

In this paper, we propose a Charuco board-based omnidirectional camera calibration method to solve the problem of conventional methods requiring overly complicated calibration procedures. Specifically, the proposed method can easily and precisely provide two-dimensional and three-dimensional coordinates of patterned feature points by arranging the omnidirectional camera in the Charuco board-based cube structure. Then, using the coordinate information of the feature points, an intrinsic calibration of each camera constituting the omnidirectional camera can be performed by estimating the perspective projection matrix. Furthermore, without an additional calibration structure, an extrinsic calibration of each camera can be performed, even though only part of the calibration structure is included in the captured image. Compared to conventional methods, the proposed method exhibits increased reliability, because it does not require additional adjustments to the mirror angle or the positions of several pattern boards. Moreover, the proposed method calibrates independently, regardless of the number of cameras comprising the omnidirectional camera or the camera rig structure. In the experimental results, for the intrinsic parameters, the proposed method yielded an average reprojection error of 0.37 pixels, which was better than that of conventional methods. For the extrinsic parameters, the proposed method had a mean absolute error of 0.90° for rotation displacement and a mean absolute error of 1.32 mm for translation displacement.

Image Matching Optimization Based on Taguchi Method and Adaptive Spatial Clustering with SIFT Features

2017 ◽  
Vol 31 (11) ◽  
pp. 1755014 ◽  
Author(s):  
Yuan Xu ◽  
Hehui Lu ◽  
Defu Zhou ◽  
Jiongbin Zheng ◽  
Jianguo Zhang
Keyword(s):  
Taguchi Method ◽  
Image Matching ◽  
Spatial Clustering ◽  
Signal To Noise Ratio ◽  
Matching Accuracy ◽  
Scale Invariant ◽  
Effect Factor ◽  
Optimum Parameters ◽  
Scale Invariant Feature ◽  
Selection Of

A novel image matching algorithm based on both Taguchi method and spatial clustering is proposed to optimize the Scale Invariant Feature Transform (SIFT) matching results. To improve the matching accuracy, adaptive spatial clustering is used. What is more, in order to get the fitting parameters to balance matching accuracy and quantity, Taguchi method is adopted to optimize the key parameter combination including the ratio threshold of Euclidean distance and the constrain parameters in the process of adaptive spatial clustering. Moreover, signal-to-noise ratio (SNR) results are analyzed by variance to get the effect factor which is taken as the basis for the selection of optimized parameters. The optimum parameters combination is obtained eventually. The final experimental results show that the matching quality based on SIFT feature are improved significantly.

Study of the Vortex-Induced Vibration of the Marine Risers With the Buoyancy

2019 ◽  
Author(s):  
Lin Zhao ◽  
Hang Su ◽  
Yanju Yin
Keyword(s):  
Vibration Frequency ◽  
Cross Flow ◽  
Experimental Results ◽  
Resonance Phenomenon ◽  
Feature Points ◽  
System A ◽  
Acceleration Amplitude ◽  
Floating System ◽  
Modal Vibration ◽  
Flow Velocities

Abstract Regarding the very large top tension of ocean deep water riser which is caused by the heavy self-weight, a innovated buoyancy system is designed. This system can effectively decrease the top tension and improve the performance of the riser movement. In order to study the upper and lower part of the floating system, a specialized model test is carried out, where the acceleration, amplitude, frequency and trajectory of the interested points along the risers are investigated. It has been observed that with the increase of the current speed, both the vibration acceleration and the vibration frequency are increasing but the bare riser amplitude is decreasing. At the speed of 0.2m/s, the resonance phenomenon is observed, but the same phenomenon is not observed for the middle floating riser subjecting to different flow velocities. At the speed of 0.4 m/s, the largest amplitude is captured. Due to the response differences of the floating riser at the up and down parts of the middle floating riser, when the amplitude is increasing, the vibration frequency is decreasing, both at cross flow (CF) direction and inline flow (IL) direction. Especially the vibration behavior of the interested points is most influenced by the buoyancy. Under different models, vibration at different flow velocities is presented along bare riser, the modal vibration effects of the floating riser will decrease In addition, according to the experiment condition, Orcaflex is applied to conduct the numerical simulation to get the vibration law of the corresponding feature points and compare it with the experimental results. The results indicate that the numerical analysis reasonably match with experimental results.

An Effective Image Matching Algorithm Based on Rotation Independence

2013 ◽  
Vol 347-350 ◽  
pp. 3685-3690
Author(s):  
Xian Ying Huang ◽  
Wei Wei Chen
Keyword(s):  
Image Matching ◽  
Irregular Shape ◽  
Matching Accuracy ◽  
Similarity Comparison ◽  
Matching Algorithm ◽  
Irregular Shapes ◽  
Irregular Region ◽  
Histogram Intersection ◽  
Intersection Method ◽  
Traditional Image

Traditional image matching algorithms has poor accuracy in image comparing, such as histogram intersection method. A new image matching algorithm based on the similarity comparison of irregular shape is presented in this paper, which divides the image into a number of irregular regions according to different colors, and extracts the boundary points of the irregular region to compose an irregular shape. The direction and distance is used to comparing the two irregular shapes if the rotation of the image is not considered, otherwise circular list is used to ignore the image rotation. It can be used widely. If two irregular shapes are similar, the two images are considered similar. Experiment proves that this method can effectively improve the image matching accuracy.

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