Leaf Vein Extract Frame Based on Mathematical Morphology

2015 ◽  
Vol 719-720 ◽  
pp. 1043-1048 ◽  
Author(s):  
Li Jia Wang ◽  
Ai Ling He ◽  
Jing Xin Guo ◽  
Hong Jun Li
Keyword(s):  
Information Processing ◽  
Edge Detection ◽  
Mathematical Morphology ◽  
Extraction Method ◽  
The Other ◽  
Scale Morphology ◽  
Gray Scale ◽  
Image Information ◽  
Leaf Vein ◽  
Union Operation

In this paper, we present a leaf vein extracting algorithm frame which deals with contour and interior vein by employing different methods. The interior vein extraction method based on gray scale processing, mathematical morphology and processing in details is presented. We apply gray-scale morphology to process the image and extract the vein information. Through the analysis of the image information, processing in details is adopted to clear the information on the other tissues and insignificant veins. The extracted significant interior vein is overlaid with the leaf contour extracted through edge detection by pixel union operation. Experiment results show the effectiveness of the proposed method.

Image Edge Extraction Based on SUSAN Operator

2014 ◽  
Vol 687-691 ◽  
pp. 3765-3768
Author(s):  
Nan Wang
Keyword(s):  
Edge Detection ◽  
High Precision ◽  
Extraction Method ◽  
The Other ◽  
Differential Detection ◽  
Edge Extraction ◽  
Image Edge ◽  
Circular Template

A new edge extraction method was put forward based on the SUSAN operator, according to the problems of poor anti-noise ability and edge detection incomplete of the conventional differential detection operator. The circular template and the center of the circle (template nuclear) were used in this method, the numbers of pixels was calculated through the comparison pixels value of template with the other points of pixels in the template circle, and then compared with the threshold, so as to the edge of images was extracted. The results showed that this method had high precision, and could be able to fully extract the edge of images. It is an effective method of extracting the edge of images.

Nondestructive Testing of Blockboard Using Combination of Wavelet Transform and Gray-Scale Mathematical Morphology

2011 ◽  
Vol 55-57 ◽  
pp. 1206-1210
Author(s):  
Nian Xue Yang ◽  
Da Wei Qi
Keyword(s):  
Wavelet Transform ◽  
Nondestructive Testing ◽  
Edge Detection ◽  
Mathematical Morphology ◽  
Noise Suppression ◽  
Testing System ◽  
Gray Scale ◽  
X Ray ◽  
Testing Method ◽  
Nondestructive Testing Method

This paper presents a scheme for blockboard nondestructive detection. X-ray nondestructive testing system has been used to obtain blockboard x-ray images. In order to recognize defects of blockboard effectively through x-ray images, an image processing method based on wavelet transform and gray-scale mathematical morphology is proposed. Firstly, image noises are reduced by wavelet soft threshold de-noising, and then a new modified mathematical morphology edge detection operator is used to detect edges of the de-noised image. The experiment results show that the method performs well in noise-suppression and edge detection. The proposed nondestructive testing method of blockboard is practical and easy to implement.

Does Performing Other Audit Tasks Affect Going-Concern Judgments?

1999 ◽  
Vol 74 (4) ◽  
pp. 493-508 ◽  
Author(s):  
Stephen E. Rau ◽  
Donald V. Moser
Keyword(s):  
Information Processing ◽  
Review Process ◽  
Negative Information ◽  
The Other ◽  
Positive Information ◽  
Going Concern ◽  
Staff Members

This study examines whether personally performing other audit tasks can bias supervising seniors' going-concern judgments. During an audit, the senior performs some audit tasks him/herself and delegates other tasks to staff members. When personally performing an audit task, the senior would focus on the evidence related to that task. We predict that such evidence will have greater influence on the senior's subsequent going-concern judgment. The results of our experiment are consistent with our predictions. When provided with an identical set of information, seniors who performed another audit task for which the underlying facts of the case reflected positively (negatively) on the company's viability, subsequently made going-concern judgments that were relatively more positive (negative). Our results also demonstrate that the well-documented tendency of auditors to attend more to negative information does not always dominate auditors' information processing. Subjects who performed the task for which the underlying facts reflected positively on the company's viability directed their attention to such positive information and, consequently, both their memory and judgments were more positive than those of subjects in the other conditions. Recent findings indicating that biases in seniors' going-concern judgments may not be fully offset in the review process are discussed along with other potential implications of our results.

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