A new image segmentation method based on Otsu method and ant colony algorithm

Lu, Jue; Rong-qiang, HU

doi:10.1109/csip.2012.6308966

Cited by 4 publications

(2 citation statements)

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“…On the other hand (Lu and Hu, 2012) proposed a combination method of Otsu and Ant Colony Optimization (ACO) algorithm in which the behavior of ants to finding a closest path from their colony to food resources has been mimicked in order to obtain a sufficient thresholding outcome. As it was demonstrated is asserted in their study the computation time is reduced significantly in compare to Otsu method.…”

Section: Related Workmentioning

confidence: 99%

A Novel Four-Directional Thresholding Approach for Lung Computed-Tomography Images by Using Similarity-Based Segmentation Technique

Heidari¹,

Abdullah²,

Abdullah³

2015

Journal of Computer Science

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Abstract:In automated pulmonary nodules extraction and lung disease diagnosis by image processing techniques, image segmentation is utilized as a primary and the most essential step of lung tumor analysis. But due to extensive similarity between pulmonary vessels, bronchus and arteries in lung region and the low contrast of the ComputedTomography (CT) image the accuracy of lung tumor diagnosis is highly dependent on the precision of segmentation. Therefore, precise lung CT image segmentation has become a challenging preprocessing task for every lung disease pathological application.In this study, a novel FourDirectional Thresholding (FDT) technique is introduced. This propounded technique segments the pulmonary parenchyma in Computed-Tomography (CT) images using the Similarity-Based Segmentation (SBS). The proposed technique aims to augment the precision of the CT image thresholding by implementing an advanced thresholding approach from four different directions in which the determination of pixels' value as being either on foreground or background is highly dependent on its adjacent pixel's intensity value and the final decision is made based on all four directions' thresholding results. In this study the importance of neighbor pixels in precision of thresholding with FDT technique is demonstrated and the effectiveness of FDT method has been evaluated on different CT images. Eventually the result of segmentation using FDT method is compared by other precursors techniques, which corroborates the high exactitude of proposed technique.

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Section: Related Workmentioning

confidence: 99%

A Novel Four-Directional Thresholding Approach for Lung Computed-Tomography Images by Using Similarity-Based Segmentation Technique

Heidari¹,

Abdullah²,

Abdullah³

2015

Journal of Computer Science

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“…Although OTSU method is an effective method in image processing, it is mostly used in Hough-Saturation-Value (HSV) regions of (Red, Green, and Blue) RGB images (Sabancı et al2018). In many radar imaging applications where the OTSU method was used, the operations were executed through the RGB image files (Işıker and Özdemir, 2019;Işıker et al, 2018;Işıker et al, 2015;Khoukhi et al2019;Lu and Hu 2012). However, converting SAR data into image files and then filtering these files again with image processing causes high computation time and data loss.…”

Section: Introductionmentioning

confidence: 99%

Clutter removal in millimeter wave GB-SAR images using OTSU’s thresholding method

Yiğit

Demirci

Özdemir

2022

International Journal of Engineering and Geosciences

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In this study, a filtering method based on the threshold value of normalized synthetic aperture radar (SAR) data is proposed to eliminate clutter in millimeter wave ground based synthetic aperture radar (GB-SAR) images. In the proposed method, first, stepped frequency continuous wave SAR data are reconstructed by using the back-projection algorithm and focused complex SAR data are obtained. Then, the amplitude values of the complex SAR data are normalized and the best threshold values to distinguish the target from clutter is determined by the OTSU's thresholding method. Next, a filter mask is created that cancels all data below the computed threshold values. The mask matrix is finally multiplied with the resulted GB-SAR data to eliminate all clutter from the image. With the proposed technique, the best threshold value is determined automatically by directly processing the raw data without converting the SAR data into any RGB images. The proposed technique is validated through real GB-SAR experiments that were carried out in the frequency band of 78-81 GHz. In the experiments, challenging GB-SAR data are obtained using high cluttered background materials, and very successful filtering operations are performed with the proposed technique.

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Ocular Biometric Measurements to Diagnose Neurological Disorders Due to Wilson Disease

et al. 2013

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A new image segmentation method based on Otsu method and ant colony algorithm

Cited by 4 publications

References 4 publications

A Novel Four-Directional Thresholding Approach for Lung Computed-Tomography Images by Using Similarity-Based Segmentation Technique

A Novel Four-Directional Thresholding Approach for Lung Computed-Tomography Images by Using Similarity-Based Segmentation Technique

Clutter removal in millimeter wave GB-SAR images using OTSU’s thresholding method

Ocular Biometric Measurements to Diagnose Neurological Disorders Due to Wilson Disease

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