Study of DEM Generation Method Based on Multi-Baseline Image Sequences in Alpine-Gorge Areas

2012 ◽  
Vol 239-240 ◽  
pp. 530-535 ◽  
Author(s):  
Hao Li ◽  
Shu Chen ◽  
Bo Su ◽  
Biao Yang
Keyword(s):  
Perspective Transformation ◽  
Measuring Method ◽  
Image Sequences ◽  
Relative Orientation ◽  
Matching Method ◽  
Initial Value ◽  
Relative Direction ◽  
Matching Process ◽  
Estimate Method ◽  
Baseline Image

Due to the peculiar terrain of Alpine and Gorge Areas, traditional measuring method is difficult to adapt. We studied on a DEM generation method based on multi-baseline image sequences including an initial value estimate method of relative direction elements based on the perspective transformation and a matching method of image sequences based on virtual epipolar plane. The experiment proves that the convergence and accuracy of relative orientation can be effectively improved by estimating the initial elements with perspective transformation. In matching process, the matching points are transferred through virtual epipolar plane. So that, we can decreased calculation redundancy and obtain multi-overlap corresponding points rapidly and accurately.

scholarly journals OPTIMIZATION ALGORITHM OF TILTED IMAGE MATCHING BASED ON ADAPTIVE INITIAL OBJECT ASPECT

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 547-554
Author(s):  
C. Zhang ◽  
Y. Ge ◽  
Q. Zhang ◽  
B. Guo
Keyword(s):  
Least Squares ◽  
Image Matching ◽  
Normal Vector ◽  
Matching Method ◽  
Initial Value ◽  
Initial State ◽  
Matching Process ◽  
Low Degree ◽  
Verification Process ◽  
Initial Object

Abstract. When adopting the matching method of the least squares image based on object-patch to match tilted images, problems like the low degree of connection points for images with the discontinuity of depth or the discrepancy in elevation or low availability of aerotriangulation points would frequently appear. To address such problems, a tilted-image-matching algorithm based on an adaptive initial object-patch is proposed by this paper. By means of the existing initial values of the interior and exterior orientation elements of the tilted image and the information of object points generated in the matching process, the algorithm takes advantage of the method of multi-patch forward intersection and object variance partition so as to adaptively calculate the elevation of the object-patch and the initial value of the normal vector direction angle. Furthermore, this algorithm aims to solve the problem of difficulties in matching the tilted image with its corresponding points brought about by the low accuracy of the initial value of the tilted image when adopting the matching method of the least squares image based on object-patch to match the tilted image with high discrepancy in elevation. We adopt the algorithm as proposed in this paper and the least squares image matching method in which the initial state of the object-patch is horizontal to the object-patch respectively to conduct the verification process of comparing and matching two groups of tilted images. Finally, the effectiveness of the algorithm as proposed in this paper is verified by the testing results.

Implementation of Verification and Matching E-KTP with Faster R-CNN and ORB

2021 ◽  
Vol 5 (4) ◽  
pp. 783-793
Author(s):  
Muhammad Muttabi Hudaya ◽  
Siti Saadah ◽  
Hendy Irawan
Keyword(s):  
Image Matching ◽  
Nearest Neighbor ◽  
Feature Matching ◽  
Image Feature ◽  
Brute Force ◽  
K Nearest Neighbor ◽  
Matching Method ◽  
Average Precision ◽  
Detection Model ◽  
Matching Process

needs a solid validation that has verification and matching uploaded images. To solve this problem, this paper implementing a detection model using Faster R-CNN and a matching method using ORB (Oriented FAST and Rotated BRIEF) and KNN-BFM (K-Nearest Neighbor Brute Force Matcher). The goal of the implementations is to reach both an 80% mark of accuracy and prove matching using ORB only can be a replaced OCR technique. The implementation accuracy results in the detection model reach mAP (Mean Average Precision) of 94%. But, the matching process only achieves an accuracy of 43,46%. The matching process using only image feature matching underperforms the previous OCR technique but improves processing time from 4510ms to 60m). Image matching accuracy has proven to increase by using a high-quality dan high quantity dataset, extracting features on the important area of EKTP card images.

scholarly journals Sistem Pendukung Keputusan Pemilihan Tenaga Kerja Indonesia (TKI) Berdasarkan Kualitas Untuk Menentukan Tempat Kerja Menggunakan Metode Profile Matching (Studi Kasus: PT Adila Prezkifarindo Duta)

2020 ◽  
Vol 1 (2) ◽  
pp. 142
Author(s):  
Dasarius Gulo
Keyword(s):  
Decision Making ◽  
Migrant Workers ◽  
Selection Process ◽  
Matching Method ◽  
Matching Process ◽  
Profile Matching ◽  
Long Time ◽  
Support Decision Making ◽  
Selection Of ◽  
The Ideal

In the process of selecting Indonesian Workers (TKI) based on quality at PT. Adila Prezkifarindo Duta is classified as still manual, where there is not yet a system for selecting quality migrant workers so it requires a long time for its assessment and the selection process is less effective. To support decision making in the selection of qualified Indonesian Workers (TKI) to make it easier by using a decision support system. One method used in the selection of qualified Indonesian Workers is the Profile Matching method. The profile matching method is a decision-making mechanism by assuming that there is an ideal level of predictor variables that must be met by applicants, rather than the minimum level that must be met or passed. In the profile matching process a process will be compared between individual competencies into standard competencies so that different competencies can be identified (also called Gap). The smaller the gap produced, the greater the weight value. In matching this profile, the selected TKI candidates are Indonesian Workers who are closest to the ideal profile of a qualified TKI.

Automatic Registration of Mobile Mapping System Lidar Points and Panoramic-Image Sequences by Relative Orientation Model

2021 ◽  
Vol 87 (12) ◽  
pp. 913-922
Author(s):  
Ningning Zhu ◽  
Bisheng Yang ◽  
Zhen Dong ◽  
Chi Chen ◽  
Xia Huang ◽  
...  
Keyword(s):  
Image Sequence ◽  
Image Sequences ◽  
Relative Orientation ◽  
Panoramic Image ◽  
Feature Points ◽  
Mobile Mapping ◽  
Orientation Model ◽  
Mapping System ◽  
Panoramic Images ◽  
Mobile Mapping System

To register mobile mapping system (MMS) lidar points and panoramic-image sequences, a relative orientation model of panoramic images (PROM) is proposed. The PROM is suitable for cases in which attitude or orientation parameters are unknown in the panoramic-image sequence. First, feature points are extracted and matched from panoramic-image pairs using the SURF algorithm. Second, these matched feature points are used to solve the relative attitude parameters in the PROM. Then, combining the PROM with the absolute position and attitude parameters of the initial panoramic image, the MMS lidar points and panoramic-image sequence are registered. Finally, the registration accuracy of the PROM method is assessed using corresponding points manually selected from the MMSlidar points and panoramic-image sequence. The results show that three types of MMSdata sources are registered accurately based on the proposed registration method. Our method transforms the registration of panoramic images and lidar points into image feature-point matching, which is suitable for diverse road scenes compared with existing methods.

scholarly journals AN IMPROVED IMAGE MATCHING METHOD BASED ON SURF ALGORITHM

2018 ◽  
Vol XLII-3 ◽  
pp. 179-184 ◽  
Author(s):  
S. J. Chen ◽  
S. Z. Zheng ◽  
Z. G. Xu ◽  
C. C. Guo ◽  
X. L. Ma
Keyword(s):  
Remote Sensing ◽  
Information Entropy ◽  
Image Matching ◽  
Feature Matching ◽  
Operating Efficiency ◽  
Similarity Function ◽  
Entropy Theory ◽  
Matching Method ◽  
Matching Process ◽  
Invariant Transformation

Many state-of-the-art image matching methods, based on the feature matching, have been widely studied in the remote sensing field. These methods of feature matching which get highly operating efficiency, have a disadvantage of low accuracy and robustness. This paper proposes an improved image matching method which based on the SURF algorithm. The proposed method introduces color invariant transformation, information entropy theory and a series of constraint conditions to increase feature points detection and matching accuracy. First, the model of color invariant transformation is introduced for two matching images aiming at obtaining more color information during the matching process and information entropy theory is used to obtain the most information of two matching images. Then SURF algorithm is applied to detect and describe points from the images. Finally, constraint conditions which including Delaunay triangulation construction, similarity function and projective invariant are employed to eliminate the mismatches so as to improve matching precision. The proposed method has been validated on the remote sensing images and the result benefits from its high precision and robustness.

High-Accuracy Modeling of Ship Deformation Based on Inertial Measuring Method

2013 ◽  
Vol 760-762 ◽  
pp. 1227-1232 ◽  
Author(s):  
Er Kai Yuan ◽  
Gong Liu Yang
Keyword(s):  
Mathematical Models ◽  
Measurement Data ◽  
Measuring Method ◽  
High Accuracy ◽  
Analysis Method ◽  
Matching Method ◽  
Precision Estimation ◽  
Set Up ◽  
Better Than ◽  
Initial Measurement

High-accuracy modeling is the key problem of ship deformation measurement based on inertial measuring method. This paper is to find a high-accuracy modeling method based on the ship deformation data measured by optical devices. According to different modeling methods, mathematical models are designed by the analysis of the initial measurement data. Wavelet analysis method is introduced in the process of modeling. Attitude matching method is selected as the simulation algorithm and Kalman filter equations are set up based on the algorithm. Simulation results show that the ship deformation can be represented accurately by mathematical models. The Precision Estimation result is better than 0.4''.

scholarly journals OD Matching of Metro IC Card Data Based on Analysis Function

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Cheng Ding ◽  
Cheng Wang ◽  
Xinyi Wang ◽  
Yueer Gao ◽  
Yongxin Liao ◽  
...  
Keyword(s):  
Function Method ◽  
Identification Accuracy ◽  
Subway Station ◽  
Matching Method ◽  
Ic Card ◽  
Matching Process ◽  
Card Number ◽  
Time Threshold ◽  
Long Time ◽  
Short Time

In the case of passengers taking the subway many times in a short time, missing cards in and out of the station, and staying in the subway station for a long time, the previous table join method cannot accurately set the time threshold parameters and correctly match the OD pairs of passengers. In order to solve these problems, an OD matching method based on analysis function is proposed in this paper. LAG () is an analytic function in Oracle which allows you to access the row at a given offset prior to the current row without using a self-join. Metro IC card dataset stores the card swiping records of passengers entering and leaving the subway station every time. In this method, the dataset is sorted in ascending order according to the card number and card swiping time, and then, the lag function of Oracle is used to take the offset of the upper line of card ID, transaction date, transaction time, in and out sign, and station ID. Finally, the matching process is completed according to the OD conditions of card number, time, and inbound and outbound sign fields. This method does not need to set a time threshold and so as to deal with the situation where passengers stay too long in the subway station. The OD matching results on in and out IC swiping cards dataset in April and May 2019 of passengers of Xiamen Metro Line verify that analysis function method has better OD matching, missing swiping identification accuracy, and effect compared to the table join method.

scholarly journals Bleach correction ImageJ plugin for compensating the photobleaching of time-lapse sequences

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 1494
Author(s):  
Kota Miura
Keyword(s):  
Time Lapse ◽  
Image Sequences ◽  
Exponential Fitting ◽  
Target Structure ◽  
Matching Method ◽  
Histogram Matching ◽  
Bleaching Condition ◽  
Set Up ◽  
Simple Ratio ◽  
Imagej Plugin

During the capturing of the time-lapse sequence of fluorescently labeled samples, fluorescence intensity exhibits decays. This phenomenon is known as 'photobleaching' and is a widely known problem in imaging in life sciences. The photobleaching can be attenuated by tuning the imaging set-up, but when such adjustments only partially work, the image sequence can be corrected for the loss of intensity in order to precisely segment the target structure or to quantify true intensity dynamics. We implemented an ImageJ plugin that allows the user to compensate for the photobleaching to estimate the non-bleaching condition with choice of three different algorithms: simple ratio, exponential fitting, and histogram matching methods. The histogram matching method is a novel algorithm for photobleaching correction. This article presents details and characteristics of each algorithm based on application to actual image sequences.

Matching Subscription Over Geo-textual Streams from IoT via Social-Aware Clustering and Apache Flink

2021 ◽  
pp. 2150295
Author(s):  
Xiaohui Huang ◽  
Ze Deng ◽  
Lizhe Wang ◽  
Tao Liu ◽  
Chengyu Zhang
Keyword(s):  
Effective Means ◽  
Spatial Relationship ◽  
Location Based Services ◽  
Acceleration Process ◽  
Matching Method ◽  
Matching Process ◽  
Current Location ◽  
Cache Strategy ◽  
The Social ◽  
Speed Up

Current location-based services (LBS) continuously generate a massive amount of geo-message streams. The cluster-based subscription matching method is an effective means to feed subscribers with related geo-messages from geo-message streaming. However, current cluster-based subscription matching methods only consider the spatial relationship and textual relationship and ignore users’ social relationship. As a result, the matching results may not completely satisfy the requirements of users. In this paper, we proposed a social-aware subscription matching method by taking spatial, textual, and social factors into consideration. Then, we used a cache strategy and a Flink-based acceleration process to reduce the extra time overhead caused by computing the social relationships. A set of extensive experiments have been conducted on a real dataset. The experimental results indicate that our method improves the recall of matching results. Besides, the Flink-based acceleration process with caching can speed up the subscription matching process by a ratio of up to 3.299 compared with the state-of-the-art.

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