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A Novel Method for Identification and Performance Improvement of Blurred and Noisy Images Using Modified Facial Deblur Inference (FADEIN) algorithms

A Novel Method for Identification and Performance Improvemen...

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IEEE Students Conference on Electrical, Electronics and Computer Science (SCEECS)

作者： Shukla, Ratnesh Kumar Das, Dipesh Agarwal, Ajay AKTU Lucknow Lucknow Uttar Pradesh India IIMT Greater Noida Greater Noida Uttar Pradesh India SRM Univ NCR Delhi Delhi India

ISBN: (纸本)9781467379182

Face Recognition is one of the most popular and powerful method of identification of the Face Recognition Systems. The identification is very important to identify the Images, Video, Graphics and Blurred and Noisy Images, Video and Graphics. Face identification has received substantial attention from researchers in face recognition, pattern recognition, biometrics, computer vision, and communities. Because of the increased attention being devoted to authentication, man machine communication, content-based image retrieval, and image coding. The problem of face identification of blurred and noisy images by relative motion between the camera and the object scene is important in a large number of applications. The solution is modified facial deblur inference (FADEIN) proposed algorithm here identifies important feature (face detection and face recognition) with which to characterize the point spread function (PSF) of the blur. The identification method is based on the concept that image characteristics along the direction and parameter motion. These are different from the characteristics in other directions. According to the PSF shape, the homogeneity and the smoothness of the blurred image in the motion direction are greater than in other directions. By registering the blurred and noisy images, we emphasize the PSF characteristics at the expense of the image characteristics. Identifies the direction and extent PSF of the blur, and evaluates its shapes. Which depends on the type of motion during the exposure. Correct Identification of the PSF feature permits better performance and accuracy of the blurred image. And compare eye, mouth, and face boundary maps to verify each face candidate. The resulting facial deblur inference model is visually similar to the store face, and proves to be quite useful for recognizing non-frontal views based on an appearance based recognition algorithm. Modified algorithm is very useful to identify the blurred and noisy images. This paper i

关键词： Blurred and Noise Image Deblur Inference Technique Wiener Filter ransac algorithm Templates Data storage Surf and Matching Functions and Face Recognition Systems

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Study on hologram mosaic algorithm based on Harris corners 7

Study on hologram mosaic algorithm based on Harris corners

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7th International Symposium on Precision Mechanical Measurements (ISPMM)

作者： Yao, Jiabao Tian, Qiuhong Sun, Zhengrong Huang, Liu Wang, Limin Zhejiang Sci Tech Univ Precis Measurement Lab 928 St 2 Hangzhou 310018 Zhejiang Peoples R China

ISBN: (纸本)9781510601673

To solve the problem of the small field of the view caused by CCD in the process of the hologram record, the hologram mosaic algorithm based on the Harris corners is proposed. The Harris corners in multi-scale are extracted and the mismatching points are removed. The final homography is calculated by using the improved ransac algorithm based on L-M algorithm. Finally, the stitched hologram with high quality can be obtained based on the weighted average fusion algorithm. It can overcome the influence to the hologram that the incident angles of the object beam are not consistent. Two experiments carried out with different reconstructed distance demonstrate that the proposed algorithm can realize the measurement of the big object by using the hologram method. Furthermore, it has high accuracy and strong robustness.

关键词： Hologram image mosaic Harris corners homography ransac algorithm L-M algorithm

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A fast iris localization algorithm under visible light condition 8

A fast iris localization algorithm under visible light condi...

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8th International Conference on Digital Image Processing (ICDIP)

作者： Liang, Guomao Wang, Shan Qu, Zhiyi Shijiazhuang Noncommissioned Officer Coll CAPF Dept Commun 2 Shijiazhuang Peoples R China Hebei Gen Hosp Cardiol Dept Shijiazhuang Peoples R China Lanzhou Univ Sch Informat Sci & Engn Lanzhou Peoples R China

ISBN: (纸本)9781510605039;9781510605046

The traditional iris localization algorithms have strict requirements on the image acquisition equipment and the light condition. When the iris images are taken in non-ideal imaging conditions, the localization precision decreases greatly or completely failed. Aiming at these problems, a fast iris localization algorithm under visible light condition is proposed in this paper. The algorithm preprocesses the eye images first. An improved starburst algorithm is then used to detect the feature points. Finally, use the least square algorithm and the ransac algorithm to locate the iris contour. The experimental results show that the algorithm is robust to the image quality and can locate the iris quickly and accurately in video image sequences.

关键词： Visible light iris localization edge detection ransac algorithm video image sequence

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The Recognition System for Zip-Top Cans in the Beverage Showcase 2

The Recognition System for Zip-Top Cans in the Beverage Show...

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2nd IEEE International Conference on Computer and Communications (ICCC)

作者： Liu Jie Du Haiqing Liu Yong Wang Kaili Beijing Univ Posts & Telecommun Beijing Lab Adv Informat Networks Beijing Peoples R China

ISBN: (纸本)9781467390262

The beverage showcase that is used to store cold drinks is ubiquitous in supermarkets, which have brought great convenience. However, a great disadvantage of the beverage showcase is that it needs manual check of remaining volume. Therefore, a recognition system is proposed in this paper to solve this tricky problem and to make our lives more intelligent. Positions, brands and the number of zip-top cans could be identified easily in the recognition system which monitors the dynamics of beverages in the beverage showcase. After starting the system, the key points detector that matches input picture and feature dataset is first executed. It will recognize zip-top cans that are less partially occluded or not covered. Next, the system carries out the rims detector to detect all upper rims of zip-top cans, which determine positions and the number of cans. In the rims detector, we propose an evaluation algorithm for the qualified ellipse. Then the colors detector detects main color blocks near the upper rims of zip-top cans to determine brands of cans covered each other. Three detectors are combined to constitute a recognition system with high accuracy and practical application value. In the system, the recognition rate is above 85%.

关键词： recognition system zip-top cans rims detector ransac algorithm evaluation algorithm

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A Coarse-to-fine Horizon Detection Method Based on Between-class Variance 9

A Coarse-to-fine Horizon Detection Method Based on Between-c...

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9th International Symposium on Computational Intelligence and Design (ISCID)

作者： Gui, Yang Lin, Dongsheng Liang, Shaojun Xu, Luoting Hong, Junxin Wuhan Mech Technol Coll Wuhan Peoples R China

ISBN: (纸本)9781509035588

A coarse-to-fine horizon detection method based on between-class variance is present. Firstly, the original image is resized to a smaller one and plenty of straight lines are selected acoording to two line parameters which are distance to image center and inclination angle in the resized image. A criterion based on the between-class variance is set up for determining the best straight line which is considered as the coarse horizon. Then several horizontal coordinates are selected in the original image equally. The points corresponding to the horizontal coordinates which are the most likely on the real horizon are found nearby the coarse horizon according to the edge information and between-class variance. Finally, ransac algorithm is applied to preserve interior points which are really on the horizon and eliminate exterior points which are not, and line parameters of the real horizon can be gained by applying least squares line fitting algorithm for all interior points. The experimental results show that the proposed method can detect out the horizons under various complicated backgrounds effectively and has many advantages such as speedy calculation, strong robustness and high engineering value.

关键词： horizon detection coarse-to-fine between-class variance ransac algorithm

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A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera

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SENSORS 2016年第10期16卷 1704-1704页

作者： Ci, Wenyan Huang, Yingping Univ Shanghai Sci & Technol Sch Opt Elect & Comp Engn Shanghai 200093 Peoples R China Nanjing Normal Univ Taizhou Colledge Sch Elect Power Engn Taizhou 225300 Peoples R China

Visual odometry estimates the ego-motion of an agent (e.g., vehicle and robot) using image information and is a key component for autonomous vehicles and robotics. This paper proposes a robust and precise method for estimating the 6-DoF ego-motion, using a stereo rig with optical flow analysis. An objective function fitted with a set of feature points is created by establishing the mathematical relationship between optical flow, depth and camera ego-motion parameters through the camera's 3-dimensional motion and planar imaging model. Accordingly, the six motion parameters are computed by minimizing the objective function, using the iterative Levenberg-Marquard method. One of key points for visual odometry is that the feature points selected for the computation should contain inliers as much as possible. In this work, the feature points and their optical flows are initially detected by using the Kanade-Lucas-Tomasi (KLT) algorithm. A circle matching is followed to remove the outliers caused by the mismatching of the KLT algorithm. A space position constraint is imposed to filter out the moving points from the point set detected by the KLT algorithm. The Random Sample Consensus (ransac) algorithm is employed to further refine the feature point set, i.e., to eliminate the effects of outliers. The remaining points are tracked to estimate the ego-motion parameters in the subsequent frames. The approach presented here is tested on real traffic videos and the results prove the robustness and precision of the method.

关键词： visual odometry ego-motion stereovision optical flow ransac algorithm space position constraint

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An Image Registration Method Based on Improved SIFT algorithm 7

An Image Registration Method Based on Improved SIFT Algorith...

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7th International Conference on Advanced Communication and Networking (ACN)

作者： Meng, Qingsong Lv, Zhihui Harbin Univ Sci & Technol Sch Automat Harbin Peoples R China

ISBN: (纸本)9781467379557

The purpose of this paper is to eliminate the mismatch points of image registration. Analyzing the SIFT algorithm and finding mismatch source, according to the source to develop solutions to eliminate the error matching points. And compared with the traditional SIFT registration results. In this paper, firstly do initial matching with SIFT algorithm, then use the feature of key points in spatial domain to eliminate the error matching, Finally, using ransac algorithm to do the final debugging. Experimental results show that the improved SIFT algorithm can better eliminate mismatch points.

关键词： image registration sift algorithm several-for-one matching ransac algorithm

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Design and Implementation of a ransac RGB-D mapping algorithm for Multi-View Point Cloud Registration

Design and Implementation of a RANSAC RGB-D mapping Algorith...

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CACS International Automatic Control Conference (CACS)

作者： Tsai, Chi-Yi Wang, Chuan-Wei Wang, Wei-Yi Tamkang Univ Dept Elect Engn Taipei 251 Taiwan

ISBN: (纸本)9781479923847;9781479923830

This paper addresses multi-view point cloud registration, which is one of the major techniques to develop a robust visual tracking system. The proposed algorithm first uses Kinect camera to capture point clouds of an object-of-interest or a complex environment with different view points. Then, a novel ransac RGB-D mapping algorithm is developed to efficiently and accurately align the multiple point clouds. Based on the aligned point cloud of the object, a CAD model can possibly be created to achieve the purpose of three-dimensional object pose estimation, which helps improving the robustness of visual tracking systems.

关键词： Multi-view point cloud registration RGB-D mapping algorithm optimization algorithm ransac algorithm

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Real Time Static/Dynamic Obstacle Detection for Visually Impaired Persons

Real Time Static/Dynamic Obstacle Detection for Visually Imp...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Tapu, R. Mocanu, B. Zaharia, T. IT Telecom SudParis ARTEMIS Dept UMR CNRS 8145 MAP5 Evry France

ISBN: (纸本)9781479912919

In this paper we introduce a novel framework for detecting static/moving obstacles in order to assist visually impaired/blind persons to navigate safely. Firstly, a set of interest points is extracted base on an image grid and tracked using the multiscale Lucas - Kanade algorithm. Next, the camera/background motion is determined through a set of homographic transforms, estimated by recursively applying the ransac algorithm on the interest point correspondence while other types of movements are identified using an agglomerative clustering technique. Finally, obstacles are classified as urgent/normal based on their distance to the subject and motion vectors orientation. The experimental results performed on various challenging scenes demonstrate that our approach is effective in videos with important camera movement, including noise and low resolution data.

关键词： feature extraction handicapped aids motion estimation object detection object tracking pattern clustering recursive estimation video cameras ransac algorithm agglomerative clustering technique blind persons camera movement camera-background motion homographic transforms image grid interest point extraction low resolution data motion vector estimation motion vector orientation multiscale Lucas-Kanade algorithm random sample consensus algorithm real-time static-dynamic obstacle detection static-moving obstacle detection visually impaired persons Cameras Classification algorithms Estimation Real-time systems Robustness Tracking Videos

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Road Network Inference from GPS Traces using DTW algorithm 17

Road Network Inference from GPS Traces using DTW Algorithm

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IEEE 17th International Conference on Intelligent Transportation Systems (ITSC)

作者： Xie, Xingzhe Philips, Wilfried Veelaert, Peter Aghajan, Hamid Univ Ghent TELIN IPI IMINDS Ghent Belgium Stanford Univ Dept Elect Engn Stanford CA 94305 USA

ISBN: (纸本)9781479960781

This paper proposes a method for inferring the road network from Global Position System (GPS) traces, which is composed of intersections and the roads between each pair of directly-connected intersections. Random Sampling (ransac) algorithm is used to cluster the turning points, where the users change their moving directions, into intersections. All of the GPS traces are segmented by the intersections, resulting in connectivity matrix of the intersections and small GPS tracks for each pair of directly-connected intersections. At last, the road between each two directly-connected intersections is extracted through aligning and averaging all of the tracks using Dynamic Time Warping (DTW) algorithm. The main novelty of our methods is aligning the tracks point by point for each road using a "stretching and compression" strategy, which not only allows road estimation by averaging the aligned tracks, but also a deeper statistical analysis using their time alignment, such as analyzing the users' speed stability at a specific location. The experimental results show that our algorithm outperforms other methods by producing clean road network without spurious edges.

关键词： Global Positioning System inference mechanisms road vehicles signal sampling statistical analysis synchronisation time warp simulation DTW algorithm GPS traces GPS tracks Global Position System ransac algorithm connectivity matrix dynamic time warping algorithm random sampling algorithm road estimation road network inference time alignment user speed stability Euclidean distance Gold Heuristic algorithms Indexes Roads Turning

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