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About 234 papers for “minimum bounding rectangle”

Cell shape as described by Minimum Bounding Rectangle (MBR).

Lee Staff (308033), Patricia Hurd (308034), Lara Reale (308035) et al. · Figshare · 2015

<p>A Typical cell shape shown within its aligned MRB (short dashed line). The rhombus (long dashed line) represents half of the area of the MBR. Also shown, is the equivalent area circle (dotted line). B This graph plots MBR Length to MBR Width for each age group (days 10, 17 and 24). Mean length∶width ratios were 1.62 (95% CI 1.58–1.65), 1.65 (95% CI 1.62–1.68), and 1.60 (95% CI 1.57–1.64) for days 10, 17, and 24 respectively. Note: the golden ratio is 1.618034. C KS Density plots of MBR length∶width ratios for each day. Length∶width ratios were clustered in the range 1 to 3. Values rarely exceeded 3, and none were found to be greater than 6. D Plots the cell areas against half of the MBR. Interestingly, the linear fits lie almost exactly in line with the <i>x = y</i> plot, i.e. cell area = half of MBR.</p>

Cited by 0Open access

An approximation based algorithm for minimum bounding rectangle computation

Jules R. Kala, Serestina Viriri, Jules‐Raymond Tapamo · 2014

Shape extraction and analysis is one of the most important task in image processing. The accuracy of the shape features extraction process increases the object recognition rate. Minimum Bounding Rectangle (MBR) is a tool that contributes to the increase of the accuracy of the shape features extraction, particularly it can be used to determine the real aspect ratio. This paper focuses on the improvement of the existing method. This is focused around the determination of the MBR's edges points, using a series of approximations. The proposed method gives more accurate MBR in all the tested situations. In order to demonstrate the accuracy of the proposed method, an experiment is setup based on the comparison of the manually drawn MBR and the ones generated by each of the methods. Results achieved showed that the proposed method outperforms existing method as it consistently produced results closest to the manually drawn MBR.

Cited by 9

Algorithm for minimum bounding rectangle based on key point set

fengqi liang, Licai Wang, Jintao Yu · 2023

This paper proposes a ship detection method based on contour extraction networks and minimum bounding box generation algorithms. The proposed method utilizes contour extraction networks to extract the contour of the ship target and generate a set of key points. Then, the minimum bounding box generation algorithm is used to transform these key points into the rotational detection box of the target, which can more accurately describe the shape and orientation of ships, thus improving the accuracy and reliability of detection. The experimental results show that the proposed method can effectively detect ships of various orientations and postures and has better performance than traditional rectangular box detection methods. The paper compares rotated bounding box detection methods based on traditional machine learning and deep learning and concludes that rotated bounding box detection methods based on deep learning can better solve the problem of ship detection in complex situations, but require a large amount of data for training and may require a higher computational cost. Finally, the paper introduces the Minimum Bounding Rectangle Algorithm used in the instance segmentation process.

Cited by 0

Tracking a minimum bounding rectangle based on extreme value theory

Marcus Baum, Uwe D. Hanebeck · KITopen · 2010

In this paper, a novel Bayesian estimator for the minimum bounding axis-aligned rectangle of a point set based on noisy measurements is derived. Each given measurement stems from an unknown point and is corrupted with additive Gaussian noise. Extreme value theory is applied in order to derive a linear measurement equation for the problem. The new estimator is applied to the problem of group target and extended object tracking. Instead of estimating each single group member or point feature explicitly, the basic idea is to track a summarizing shape, namely the minimum bounding rectangle, of the group. Simulation results demonstrate the feasibility of the estimator.

Cited by 8Open access

Research on Jewelry Positioning Technology Based on Minimum Bounding Rectangle

HOU Zhanwei,JIA Yulan,WANG Zhiheng · SHILAP Revista de lepidopterología · 2016

The length and width of the irregular object is difficult to be unified in an image,and the traditional detection algorithm is not accurate enough.For this problem,this paper states an automatic location detection algorithm.In order to obtain the minimum bounding rectangle of the jewelry,firstly it estimates the target direction of the principal axis and the initial target rectangle related to the principal axis,following by finding out the optimal rectangle profile with the center of rotation formatted by the initial rectangle’s geometric center.It performs translational optimization on the rotated shape of rectangle to achieve the final positioning of the jewelry outline.Experimental results show that this algorithm is more accurate than the existing minimum rectangle algorithm MBR for the detection of irregular object in capable to locate the exact jewelry outline.

Cited by 0Open access

Minimum Bounding Rectangle dan Aplikasinya pada Pemetaan Efektif Area Terdampak Bencana

Izzati, Fulqi · Andalas University eThesis (Andalas University) · 2024

Pemetaan area terdampak bencana merupakan langkah penting dalam upaya mitigasi dan penanganan bencana. Salah satu metode yang dapat digunakan untuk melakukan pemetaan secara efisien adalah Minimum Bounding Rectangle (MBR), yang memungkinkan representasi area terdampak secara lebih sederhana dan efektif. Penelitian ini bertujuan mengaplikasikan metode MBR menggunakan pemrograman Python, untuk menghasilkan pemetaan yang akurat dan dapat diimplementasikan dalam sistem manajemen bencana. Selain itu, penelitian ini juga mengevaluasi efektivitas metode MBR dalam mengidentifikasi wilayah terdampak bencana berdasarkan data area terdampak yang diperoleh dari citra satelit. Hasil dari penelitian ini diharapkan dapat memberikan kontribusi dalam mempercepat proses pengambilan keputusan terkait penanganan bencana, serta meningkatkan efisiensi dalam alokasi sumber daya.

Cited by 0Open access

Comparison of the Minimum Bounding Rectangle and Minimum Circumscribed Ellipse of Rain Cells from TRMM

Hongke Cai, Ya Mao, Xinran Zhu et al. · 2025

Based on the TRMM dataset, this paper compares the applicability of the improved MCE (minimum circumscribed ellipse), MBR (minimum bounding rectangle), and DIA (direct indexing area) methods for rain cell fitting. These three methods can reflect the geometric characteristics of clouds and apply geometric parameters to estimate the real dimensions of rain cells. The MCE method shows a major advantage in identifying the circumference of rain cells. The circumference of rain cells identified by MCE in most samples is smaller than that identified by DIA and MBR, and more similar to the observed rain cells. The area of rain cells identified by MBR is relatively robust. For rain cells composed of many pixels (N > 20), the overall performance is better than that of MCE, but the contribution of MBR to the best identification results, which have the shortest circumference and the smallest area, is less than that of MCE. The DIA method is best suited to small rain cells with a circumference of less than 100 km and an area of less than 120 km2, but the overall performance is mediocre. The MCE method tends to achieve the highest success at any angle, whereas there are fewer “best identification” results from DIA or MBR and more of the worst ones in the along-track direction and cross-track direction. Through this comprehensive comparison, we conclude that MCE can obtain the best fitting results with the shortest circumference and the smallest area on behalf of the high filling effect for all sizes of rain cells.

Cited by 0Open access

AUTOMATIC 3D BUILDING MODEL GENERATION FROM LIDAR AND IMAGE DATA USING SEQUENTIAL MINIMUM BOUNDING RECTANGLE

Eunju Kwak, M. Al-Durgham, Ayman Habib · ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · 2012

Abstract. Digital Building Model is an important component in many applications such as city modelling, natural disaster planning, and aftermath evaluation. The importance of accurate and up-to-date building models has been discussed by many researchers, and many different approaches for efficient building model generation have been proposed. They can be categorised according to the data source used, the data processing strategy, and the amount of human interaction. In terms of data source, due to the limitations of using single source data, integration of multi-senor data is desired since it preserves the advantages of the involved datasets. Aerial imagery and LiDAR data are among the commonly combined sources to obtain 3D building models with good vertical accuracy from laser scanning and good planimetric accuracy from aerial images. The most used data processing strategies are data-driven and model-driven ones. Theoretically one can model any shape of buildings using data-driven approaches but practically it leaves the question of how to impose constraints and set the rules during the generation process. Due to the complexity of the implementation of the data-driven approaches, model-based approaches draw the attention of the researchers. However, the major drawback of model-based approaches is that the establishment of representative models involves a manual process that requires human intervention. Therefore, the objective of this research work is to automatically generate building models using the Minimum Bounding Rectangle algorithm and sequentially adjusting them to combine the advantages of image and LiDAR datasets.

Cited by 21Open access

A building polygonal object matching method based on minimum bounding rectangle combinatorial optimization and relaxation labeling

Lingjia Liu, Zhiyi Fu, Yu Xia et al. · Transactions in GIS · 2023

Abstract Volunteered geographic information (VGI) is an emerging phenomenon where anyone can create geographic information and share it with others. Compared with traditional authoritative geospatial data, it has several advantages, such as enriched data, instant updates, and low cost. The object matching method is widely used in VGI quality assessment and data updates. However, VGI matching faces certain challenges, such as the levels of detail that vary from object to object, the uneven distribution of data quality, and the automated matching requirement. To resolve these problems, this article proposes a new matching method that effectively combines the advantages of minimum bounding rectangle combinatorial optimization (MBRCO) and relaxation labeling. The proposed method (1) avoids setting the similarity threshold and weights and does not require training samples. This process is realized based on contextual information and optimization. (2) It overcomes the disadvantage that the MBRCO algorithm cannot distinguish adjacent buildings with similar shapes. Our approach is experimentally validated using two publicly available spatial datasets: OpenStreetMap and AutoNavi map. The experimental studies show that the proposed automatic matching method outperforms all the threshold‐based MBRCO methods and achieves high accuracy with a precision of 97.8% and a recall of 99.2%.

Cited by 6Open access

A New K-NN Query Algorithm Based on the Clustering and Sorting of Minimum Bounding Rectangle

Guobin Li, Jine Tang · 2010

The K-neighbor query algorithm is an important class of search algorithm in the spatial database, this paper will adopt the K-means algorithm to carry on sorting to the smallest enclosing rectangle in accordance with orientation relationship based on the measurement of distance and pruning strategies of MBR in the traditional K-nearest neighbor query, it can carry on the K-neighbor queries after sorting, as a result, the new algorithm can omit the need of a great amount of distance calculation between the queried object and the MBR as well as the need of the judgment when carry on pruning, the experiment shows that the algorithm query efficiency is enhanced, and has a wide range of applications in practice.

Cited by 2

Quadrant-Based Minimum Bounding Rectangle-Tree Indexing Method for Similarity Queries over Big Spatial Data in HBase

Bumjoon Jo, Sungwon Jung · Sensors · 2018

With the rapid development of mobile devices and sensors, effective searching methods for big spatial data have recently received a significant amount of attention. Owing to their large size, many applications typically store recently generated spatial data in NoSQL databases such as HBase. As the index of HBase only supports a one-dimensional row keys, the spatial data is commonly enumerated using linearization techniques. However, the linearization techniques cannot completely guarantee the spatial proximity of data. Therefore, several studies have attempted to reduce false positives in spatial query processing by implementing a multi-dimensional indexing layer. In this paper, we propose a hierarchical indexing structure called a quadrant-based minimum bounding rectangle (QbMBR) tree for effective spatial query processing in HBase. In our method, spatial objects are grouped more precisely by using QbMBR and are indexed based on QbMBR. The QbMBR tree not only provides more selective query processing, but also reduces the storage space required for indexing. Based on the QbMBR tree index, two query-processing algorithms for range query and kNN query are also proposed in this paper. The algorithms significantly reduce query execution times by prefetching the necessary index nodes into memory while traversing the QbMBR tree. Experimental analysis demonstrates that our method significantly outperforms existing methods.

Cited by 11Open access

Edam: An Efficient Clique Discovery Algorithm

With Frequency Transformation, Yifei Ma, Guoren Wang et al. · 2006

this paper, we propose an efficient algorithm, EDAM, for finding motifs based on frequency transformation and Minimum Bounding Rectangle (MBR) techniques

Cited by 0

A perspective correction method based on the bounding rectangle and least square fitting

Bao Yang, Jesse S. Jin, Fei Li et al. · 2016

Although Automatic License Plate Recognition (ALPR) systems have achieved high recognition speed and efficiency, perspective distortion may still affect the accuracy and reliability of ALPR due to the uncertainty of camera shooting angle. Some existing license plate correction methods are computational expensive and low robust. We proposed a perspective correction method based on the bounding rectangle and least square fitting. We extracted the bounding rectangle and the minimum bounding rectangle of each character. We use the least square method to fit a line for key points. Finally, the approach uses four vertices of license plate to get perspective transformation matrix and correct the distorted images. The results of our experiments show that our method is fast, accurate and robust.

Cited by 7

The process of trachea/bronchus removing and lung contour refining.

Xiaolei Liao (2993637), Juanjuan Zhao (300644), Cheng Jiao (2993634) et al. · Figshare · 2016

<p>(a) Binarization of the coarse lung image; (b) Extraction of minimum bounding rectangle; (c) Select seed points with the LRS algorithm; (d) Final lung mask.</p>

Cited by 0Open access