Segmentation of medical images with Canny operator and GVF snake model

Cheng, Jinyong; Xue, Ruojuan; Lü, Wenpeng; Jia, Ruixiang

doi:10.1109/wcica.2008.4593191

Cited by 10 publications

(2 citation statements)

References 16 publications

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“…In their method, Canny established that an edge detector must essentially satisfy three basic performance criteria: Good detection, good location and good response. Cheng et al (2008) described, in other words, that the Canny operator aims reduce the error rate while minimizing the number of false positives (pixels that do not represent edges detected) and false negatives (pixels representing edges, but which are not detected); minimize the distance between the detected edge and the real edge of the image processed; minimize the likelihood of multiple responses to a single edge.…”

Section: Laplacian Of Gaussianmentioning

confidence: 99%

Comparison of Edge Detection Techniques Applied in the Identification of Centerline Segregation on Steel Slabs

Queiroz¹,

Hirakawa²

2015

American Journal of Applied Sciences

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The method Baumann, or Sulphur print as it is also known, is one of the tools used to evaluate the operating conditions of continuous casting machine and quality control of the production of steel slabs. The correct evaluation of centerline segregation severity, analyzed in Sulphur print, is essential to control this process. However, given the classification complexity between the different severity levels, the classification process becomes dependent on experts experience and knowledge. In the light of human interference in this analysis, differences on classification results are possible, since the activity is manual and occasionally an expert can be stricter than others during the classification process. The evaluation of this scenario has motivated the search for the development of computational resources able to identify and classify the defect of centerline segregation. The edge detection techniques are applied to identify the centerline segregation, to reduce the amount of data to be processed and discard information considered irrelevant image while preserving the structural features of the regions of interest that will be used later to classify the severity of the defect. This paper presents a comparison between Sobel, Laplacian of Gaussian and Canny edge detection methods applied to the digital images of the samples generated during Baumann method for identifying the defect of centerline segregation.

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Section: Laplacian Of Gaussianmentioning

confidence: 99%

Comparison of Edge Detection Techniques Applied in the Identification of Centerline Segregation on Steel Slabs

Queiroz¹,

Hirakawa²

2015

American Journal of Applied Sciences

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“…Leaves are the organs where photosynthesis takes place, and the morphological features of leaves represent an important aspect of plant growth status [1]. Shape is one major morphological feature of leaves [2][3][4][5][6][7], and edge extraction of leaves is one step towards leaf shape extraction.…”

Section: Introductionmentioning

confidence: 99%

Non-invasive Edge Detection of Leaves Based on Order Morphology

Zhang

et al. 2019

Computer and Computing Technologies in Agriculture XI

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Non-invasive edge detection of leaves is the key step of leaf feature extraction. Traditional algorithms for edge detection of leaves are usually invasive, since the detection is carried out after the leaves are picked. We apply order morphology in this study to non-invasive edge detection of leaves.First we analyze the algorithm for order morphology edge detection of leaves. In particular, the impact of structural elements and percentile on the detection is discussed. Based on the theory of order morphology transform of leaf images, the operator for detecting the leaf edge is constructed. Finally simulation experiment is carried out on leaf images under the conditions of natural illumination and artificial noise, respectively. Results show that the proposed algorithm is accurate and fast in leaf edge extraction and not sensitive to noise.

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