Graph Approach in Image Segmentation

Guada, Carely; Gómez, Daniel; Rodríguez, J. Tinguaro; Yáñez, Javier; Montero, Javier

doi:10.1007/978-3-319-66824-6_18

Cited by 1 publication

(2 citation statements)

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“…It should be noted that, in the past few years, several other studies related to this research topic have been conducted in references. [11][12][13][14] The above-mentioned algorithms were studied only for specific, special engineering images; however, none of the existing image segmentation algorithms can be standard. Based on our experiments, for the images in this study, the effect of these previously algorithms is not ideal.…”

Section: Introductionmentioning

confidence: 99%

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Image segmentation by improved minimum spanning tree with fractional differential and Canny detector

Lin

Guo

Yan

et al. 2019

Journal of Algorithms & Computational Technology

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In this study, we propose an algorithm that uses an improved Minimum Spanning Tree algorithm and a modified Canny edge detector to segment images that contain a considerable amount of noises. First, we use our modified Canny operator to pre-process an image, and record the obtained object boundary information; then, we apply the improved Minimum Spanning Tree algorithm to associate the above information with boundary points in order to separate edges into two classes in the image, namely the inner and boundary regions. In particular, Minimum Spanning Tree algorithm is improved by using Fractional differential and combining the functions of the intra-regional and interregional differences with a function for edge weights. Based on the experimental results, compared with the other four exiting algorithms, the new algorithm has the higher accuracy and the better effect for noised image segmentation.

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Section: Introductionmentioning

confidence: 99%

“…It should be noted that, in the past few years, several other studies related to this research topic have been conducted in references. 11–14…”

Section: Introductionmentioning

confidence: 99%