Damage assessment for slopes using geographical information system(GIS) has been actively carried out by researchers working on several government organizations and research institutes in Korea. In this study, 596 slo...Damage assessment for slopes using geographical information system(GIS) has been actively carried out by researchers working on several government organizations and research institutes in Korea. In this study, 596 slope damages were examined to identify the types of damage associated with dip angles, dip directions, and heavy rainfall resulting from typhoons in South Korea. Heavy rainfall of 100 mm to 300 mm resulted in 80% at the investigated slope damages. A GIS database was developed for highways, rainfall, soil or rock geometry, and types of damage. A grid of rainfall intensity was generated from the records of maximum daily rainfall. Contours for slope damages and heavy rainfall using optimal GIS mesh dimensions were generated to visualize damage patterns and show substantially strong correlation of rainfall with slope damages. The combination of remote sensing with the GIS pattern recognition process described in this work are being expanded for a new generation of emergency response and rapid decision support systems.展开更多
Extracting the cell objects of red tide algae is the most important step in the construction of an automatic microscopic image recognition system for harmful algal blooms.This paper describes a set of composite method...Extracting the cell objects of red tide algae is the most important step in the construction of an automatic microscopic image recognition system for harmful algal blooms.This paper describes a set of composite methods for the automatic segmentation of cells of red tide algae from microscopic images.Depending on the existence of setae,we classify the common marine red tide algae into non-setae algae species and Chaetoceros,and design segmentation strategies for these two categories according to their morphological characteristics.In view of the varied forms and fuzzy edges of non-setae algae,we propose a new multi-scale detection algorithm for algal cell regions based on border-correlation,and further combine this with morphological operations and an improved GrabCut algorithm to segment single-cell and multicell objects.In this process,similarity detection is introduced to eliminate the pseudo cellular regions.For Chaetoceros,owing to the weak grayscale information of their setae and the low contrast between the setae and background,we propose a cell extraction method based on a gray surface orientation angle model.This method constructs a gray surface vector model,and executes the gray mapping of the orientation angles.The obtained gray values are then reconstructed and linearly stretched.Finally,appropriate morphological processing is conducted to preserve the orientation information and tiny features of the setae.Experimental results demonstrate that the proposed methods can effectively remove noise and accurately extract both categories of algae cell objects possessing a complete shape,regular contour,and clear edge.Compared with other advanced segmentation techniques,our methods are more robust when considering images with different appearances and achieve more satisfactory segmentation effects.展开更多
基金supported by the 2012 Inje University research grant
文摘Damage assessment for slopes using geographical information system(GIS) has been actively carried out by researchers working on several government organizations and research institutes in Korea. In this study, 596 slope damages were examined to identify the types of damage associated with dip angles, dip directions, and heavy rainfall resulting from typhoons in South Korea. Heavy rainfall of 100 mm to 300 mm resulted in 80% at the investigated slope damages. A GIS database was developed for highways, rainfall, soil or rock geometry, and types of damage. A grid of rainfall intensity was generated from the records of maximum daily rainfall. Contours for slope damages and heavy rainfall using optimal GIS mesh dimensions were generated to visualize damage patterns and show substantially strong correlation of rainfall with slope damages. The combination of remote sensing with the GIS pattern recognition process described in this work are being expanded for a new generation of emergency response and rapid decision support systems.
基金Supported by the National Natural Science Foundation of China(Nos.61301240,61271406)
文摘Extracting the cell objects of red tide algae is the most important step in the construction of an automatic microscopic image recognition system for harmful algal blooms.This paper describes a set of composite methods for the automatic segmentation of cells of red tide algae from microscopic images.Depending on the existence of setae,we classify the common marine red tide algae into non-setae algae species and Chaetoceros,and design segmentation strategies for these two categories according to their morphological characteristics.In view of the varied forms and fuzzy edges of non-setae algae,we propose a new multi-scale detection algorithm for algal cell regions based on border-correlation,and further combine this with morphological operations and an improved GrabCut algorithm to segment single-cell and multicell objects.In this process,similarity detection is introduced to eliminate the pseudo cellular regions.For Chaetoceros,owing to the weak grayscale information of their setae and the low contrast between the setae and background,we propose a cell extraction method based on a gray surface orientation angle model.This method constructs a gray surface vector model,and executes the gray mapping of the orientation angles.The obtained gray values are then reconstructed and linearly stretched.Finally,appropriate morphological processing is conducted to preserve the orientation information and tiny features of the setae.Experimental results demonstrate that the proposed methods can effectively remove noise and accurately extract both categories of algae cell objects possessing a complete shape,regular contour,and clear edge.Compared with other advanced segmentation techniques,our methods are more robust when considering images with different appearances and achieve more satisfactory segmentation effects.
