scholarly journals Generation of Homogeneous Slope Units Using a Novel Object-Oriented Multi-Resolution Segmentation Method

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3422
Author(s):  
Yange Li ◽  
Jianhua He ◽  
Fang Chen ◽  
Zheng Han ◽  
Weidong Wang ◽  
...  
Keyword(s):  
Image Processing ◽  
Sensitivity Analysis ◽  
Image Segmentation ◽  
Landslide Susceptibility ◽  
Object Oriented ◽  
Segmentation Method ◽  
Novel Object ◽  
Digital Elevation

The generation of map units is a fundamental step for an appropriate assessment of landslide susceptibility. Recent studies have indicated that the terrain relief-based slope units perform better in homogeneity compared with the grid units. However, it is difficult at present to generate high-precision and high-matching slope units by traditional methods. The problem commonly concentrates in the plain areas without obvious terrain reliefs and the junction of sudden changes in terrain. In this paper, we propose a novel object-oriented segmentation method for generating homogeneous slope units. Herein, the multi-resolution segmentation algorithm in the image processing field is introduced, enabling the integration of terrain boundary conditions and image segmentation conditions in slope units. In order to illustrate the performances of the proposed method, Kitakyushu region in Japan is selected as a case study. The results show that the proposed method generates satisfactory slope units that satisfactorily reproduce the actual terrain relief, with the best within-unit and between-unit homogeneities compared with the previous methods, in particular at the plain areas. We also verify the effectiveness of the presented method through the sensitivity analysis using different resolutions of digital elevation models (DEMs) data of the region. It is reported that the presented approach is notably advanced in the requirements of the quality of DEM data, as the presented approach is less sensitive to DEM spatial resolution compared with other available methods.

scholarly journals The performance of landslide susceptibility models critically depends on the quality of digital elevation models

2020 ◽  
Vol 11 (1) ◽  
pp. 1075-1092 ◽  
Author(s):  
Jonas Brock ◽  
Patrick Schratz ◽  
Helene Petschko ◽  
Jannes Muenchow ◽  
Mihai Micu ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Digital Elevation Models ◽  
Digital Elevation

Comparison of Thresholding and Edge Detection Segmentation Techniques

2013 ◽  
Vol 860-863 ◽  
pp. 2783-2786
Author(s):  
Yu Bing Dong ◽  
Hai Yan Wang ◽  
Ming Jing Li
Keyword(s):  
Image Segmentation ◽  
Root Mean Square Error ◽  
Edge Detection ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Experimental Results ◽  
Mean Square ◽  
Segmentation Method ◽  
Segmentation Algorithms

Edge detection and thresholding segmentation algorithms are presented and tested with variety of grayscale images in different fields. In order to analyze and evaluate the quality of image segmentation, Root Mean Square Error is used. The smaller error value is, the better image segmentation effect is. The experimental results show that a segmentation method is not suitable for all images segmentation.

PDE-Based Image Processing

2012 ◽  
pp. 49-89
Author(s):  
Rajeev Srivastava
Keyword(s):  
Image Processing ◽  
Image Restoration ◽  
Shape From Shading ◽  
Surface Geometry ◽  
Partial Differential ◽  
Basic Concepts ◽  
Processing Techniques ◽  
Image Modelling

This chapter describes the basic concepts of partial differential equations (PDEs) based image modelling and their applications to image restoration. The general basic concepts of partial differential equation (PDE)-based image modelling and processing techniques are discussed for image restoration problems. These techniques can also be used in the design and development of efficient tools for various image processing and vision related tasks such as restoration, enhancement, segmentation, registration, inpainting, shape from shading, 3D reconstruction of objects from multiple views, and many more. As a case study, the topic in consideration is oriented towards image restoration using PDEs formalism since image restoration is considered to be an important pre-processing task for 3D surface geometry, reconstruction, and many other applications. An image may be subjected to various types of noises during its acquisition leading to degraded quality of the image, and hence, the noise must be reduced. The noise may be additive or multiplicative in nature. Here, the PDE-based models for removal of both types of noises are discussed. As examples, some PDE-based schemes have been implemented and their comparative study with other existing techniques has also been presented.

scholarly journals A Multiscale CNN-CRF Framework for Environmental Microorganism Image Segmentation

2020 ◽  
Vol 2020 ◽  
pp. 1-27
Author(s):  
Jinghua Zhang ◽  
Chen Li ◽  
Frank Kulwa ◽  
Xin Zhao ◽  
Changhao Sun ◽  
...  
Keyword(s):  
Image Segmentation ◽  
State Of The Art ◽  
Conditional Random Field ◽  
Segmentation Method ◽  
Recall Accuracy ◽  
Evaluation Indexes ◽  
Segmentation Quality ◽  
Segmentation Approach ◽  
Overall Evaluation

To assist researchers to identify Environmental Microorganisms (EMs) effectively, a Multiscale CNN-CRF (MSCC) framework for the EM image segmentation is proposed in this paper. There are two parts in this framework: The first is a novel pixel-level segmentation approach, using a newly introduced Convolutional Neural Network (CNN), namely, “mU-Net-B3”, with a dense Conditional Random Field (CRF) postprocessing. The second is a VGG-16 based patch-level segmentation method with a novel “buffer” strategy, which further improves the segmentation quality of the details of the EMs. In the experiment, compared with the state-of-the-art methods on 420 EM images, the proposed MSCC method reduces the memory requirement from 355 MB to 103 MB, improves the overall evaluation indexes (Dice, Jaccard, Recall, Accuracy) from 85.24%, 77.42%, 82.27%, and 96.76% to 87.13%, 79.74%, 87.12%, and 96.91%, respectively, and reduces the volume overlap error from 22.58% to 20.26%. Therefore, the MSCC method shows great potential in the EM segmentation field.

scholarly journals Sensitivity analysis of the DEM resolution and effective parameters of runoff yield in the SWAT model: a case study

2019 ◽  
Vol 69 (1) ◽  
pp. 39-54 ◽  
Author(s):  
Mohammad Nazari-Sharabian ◽  
Masoud Taheriyoun ◽  
Moses Karakouzian
Keyword(s):  
Sensitivity Analysis ◽  
Assessment Tool ◽  
Swat Model ◽  
Computation Time ◽  
Effective Parameters ◽  
Digital Elevation ◽  
Elevation Model ◽  
The Impact ◽  
Reduce Computation Time

Abstract This study investigates the impact of different digital elevation model (DEM) resolutions on the topological attributes and simulated runoff, as well as the sensitivity of runoff parameters in the Mahabad Dam watershed in Iran. The watershed and streamlines were delineated in ArcGIS, and the hydrologic analyses were performed using the Soil and Water Assessment Tool (SWAT). The sensitivity analysis on runoff parameters was performed, using the Sequential Uncertainties FItting Ver. 2 algorithm, in the SWAT Calibration and Uncertainty Procedures (SWAT-CUP) program. The results indicated that the sensitivity of runoff parameters, watershed surface area, and elevations changed under different DEM resolutions. As the distribution of slopes changed using different DEMs, surface parameters were most affected. Furthermore, higher amounts of runoff were generated when DEMs with finer resolutions were implemented. In comparison with the observed value of 8 m3/s at the watershed outlet, the 12.5 m DEM showed more realistic results (6.77 m3/s). Comparatively, the 12.5 m DEM generated 0.74% and 2.73% more runoff compared with the 30 and 90 m DEMs, respectively. The findings of this study indicate that in order to reduce computation time, researchers may use DEMs with coarser resolutions at the expense of minor decreases in accuracy.

A Video Image Segmentation Technology Based on Adaptive Thresholding Algorithm

2013 ◽  
Vol 380-384 ◽  
pp. 1189-1192 ◽  
Author(s):  
Hai Jun Zhao
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Variance Decomposition ◽  
Optimum Number ◽  
Segmentation Method ◽  
Class Difference ◽  
Classification Image ◽  
Maximum Variance ◽  
Important Position ◽  
Thresholding Algorithm

Image segmentation is a key step in image processing and image analysis and occupies an important position in image engineering.In this paper, basing on maximum variance between-class, an adaptive and multi-objective image segmentation method is proposed. The concrete implement is to determine adaptively the optimum number of threshold of image using the idea of variance decomposition,while calculating the weighted ratio of within class difference and class difference existing in each classification image. By comparing the ratio, the optimum number of target for image can be get. The experimental results show that the sub-images after segmentation are relatively clear and the differences between classes are obvious.

FEATURE EXTRACTION BY RANK-ORDER FILTERING FOR IMAGE SEGMENTATION

1988 ◽  
Vol 02 (02) ◽  
pp. 301-319 ◽  
Author(s):  
P. ZAMPERONI
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Image Segmentation ◽  
Density Function ◽  
Rank Order ◽  
Experimental Results ◽  
Textural Features ◽  
Segmentation Method ◽  
Unified Approach

The aim of this paper is to outline a unified approach to feature extraction for segmentation purposes by means of the rank-order filtering of grey values in a neighbourhood of each pixel of a digitized image. In the first section an overview of rank-order filtering for image processing is given, and a fast histogram algorithm is proposed. Section 2 deals with the extraction of a “locally most representative grey value”, defined as the maximum of the local histogram density function. In Section 3 several textural features are described, which can be extracted from the local histogram by means of rank-order filtering, and their properties are discussed. Section 4 formulates some general requirements to be met by the process of image segmentation, and describes a method based upon the features introduced in the former sections. In the last section some experimental results applied to aerial views obtained with the segmentation method of Sect. 4 are reported. These test images have been analyzed within the scope of an investigation centered on terrain recognition for agricultural and ecological purposes.

scholarly journals AUTOMATIC DETERMINATION OF SEEDS FOR RANDOM WALKER BY SEEDED WATERSHED TRANSFORM FOR TUNA IMAGE SEGMENTATION

2018 ◽  
Vol 11 (1) ◽  
pp. 52 ◽  
Author(s):  
Moch Zawaruddin Abdullah ◽  
Dinial Utami Nurul Qomariah ◽  
Lafnidita Farosanti ◽  
Agus Zainal Arifin
Keyword(s):  
Image Segmentation ◽  
Image Classification ◽  
Misclassification Error ◽  
Segmentation Method ◽  
Automatic Determination ◽  
Tuna Fish ◽  
Watershed Transform ◽  
Random Walker

Tuna fish image classification is an important part to sort out the type and quality of the tuna based upon the shape. The image of tuna should have good segmentation results before entering the classification stage. It has uneven lighting and complex texture resulting in inappropriate segmentation. This research proposed method of automatic determination seeded random walker in the watershed region for tuna image segmentation. Random walker is a noise-resistant segmentation method that requires two types of seeds defined by the user, the seed pixels for background and seed pixels for the object. We evaluated the proposed method on 30 images of tuna using relative foreground area error (RAE), misclassification error (ME), and modified Hausdroff distances (MHD) evaluation methods with values of 4.38%, 1.34% and 1.11%, respectively. This suggests that the seeded random walker method is more effective than exiting methods for tuna image segmentation.

scholarly journals SISTEM INFORMASI PEMESANAN PEMENTASAN SENI TARI BERBASIS WEBSITE STUDI KASUS SANGGAR CANGGET BUDAYA KOTABUMI LAMPUNG UTARA

2018 ◽  
Vol 6 (2) ◽  
pp. 21-28
Author(s):  
Rima Mawarn ◽  
Rianda Venia Audina
Keyword(s):  
Evaluation System ◽  
System Development ◽  
Object Oriented ◽  
System Evaluation ◽  
Use Case ◽  
Development Method ◽  
Evaluation Test ◽  
Class Diagrams

ABSTRACTSanggar Cangget Culture is an organization engaged in the art of dance.To provide a better service and the latest information to customers, its products are in need of a system that can be accessed by customers from anywhere.This system will make it easier for customers to obtain information or obtain a service.As for development used in this research is the Object Oriented model using several tools such as Use Case, Activity Diagrams, Class diagrams and Squence Diagram.And for system development method that is used is the method Prototype/Prototyping.The method Prototype/Prototyping is the sequence of activities that started from the collection needs, build a prototyping, prototyping, evaluation, test systems encode system, evaluation system and the use of the system.Expected by the existing Systems of information Ordering Performances Dance Studio Case Study-based websites Cangget Kotabumi North Lampung Culture makes it easy for users to order dance anywhere over the internet and can be connected to improve the performance and quality of service.

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