Automatic thresholding of gray-level pictures using two-dimension Otsu method

Liu, Jianzhuang; Li, Wenqing; Tian, Yupeng

doi:10.1109/ciccas.1991.184351

Cited by 116 publications

(72 citation statements)

References 1 publication

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“…1(a)-(d). The tracked segmented region is binarised using 2D Otsu automatic thresholding technique [38], which utilises both the grey level information of each pixel and its spatial correlation information within the 2D neighbourhood to outperform the Otsu method [39] in the presence of noise for extracting the subject's silhouette as illustrated in Fig. 1(e).…”

Section: Module 1: Silhouette Extraction and Postprocessingmentioning

confidence: 99%

Silhouette-based gait recognition using Procrustes shape analysis and elliptic Fourier descriptors

Das

Tjahjadi

2012

Pattern Recognition

101

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This paper presents a gait recognition method which combines spatio-temporal motion characteristics, statistical and physical parameters (referred to as STM-SPP) of a human subject for its classification by analysing shape of the subject's silhouette contours using Procrustes shape analysis (PSA) and elliptic Fourier descriptors (EFDs). STM-SPP uses spatio-temporal gait characteristics and physical parameters of human body to resolve similar dissimilarity scores between probe and gallery sequences obtained by PSA. A part-based shape analysis using EFDs is also introduced to achieve robustness against carrying conditions. The classification results by PSA and EFDs are combined, resolving tie in ranking using contour matching based on Hu moments. Experimental results show STM-SPP outperforms several silhouette-based gait recognition methods.

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Section: Module 1: Silhouette Extraction and Postprocessingmentioning

confidence: 99%

Silhouette-based gait recognition using Procrustes shape analysis and elliptic Fourier descriptors

Das

Tjahjadi

2012

Pattern Recognition

101

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“…Following thresholding and binarisation of each of the acquired images, the ensemble average image and the corresponding standard deviation were calculated at given time instances over all acquired injection events and for all transparent nozzle tips, applying equations 1a,b; where I represents a single pixel intensity value, I represents mean pixel intensity value and N is the number of samples. A robust post-processing procedure was secured by an automated selection of the binarisation threshold that was based on a 2-dimensional histogram approach found in [32]; this method is an extension of the well-known threshold selection method from grey-level histograms of Otsu, [33]. Given the applied post-processing method and the number of samples used, the calculated statistical uncertainty is 0.2%.…”

Section: Experimental Set Up and Techniquementioning

confidence: 99%

Instantaneous and ensemble average cavitation structures in Diesel micro-channel flow orifices

Mitroglou

McLorn

Gavaises

et al. 2014

Fuel

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“…To solve this difficulty Otsu [7] proposed discriminant analysis to maximize the separability of the resultant classes. Interaction among the pixels is also a reasonable feature tried in two-dimensional Otsu method [8]. In entropy based algorithms proposed by Kapur et al [10] extend the previous work of pun [9] that first uses the concept of entropy for thresholding.…”

Section: IImentioning

confidence: 94%

Segmentation by Thresholding on Medical Imaging – A Survey

Malarvizhi¹

2017

IJRASET

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Medical imaging is one of the important topics in research field. It is the visualization of body parts, tissues, or organs, for use in clinical diagnosis, treatment and disease monitoring. Imaging techniques encompass the fields of radiology, nuclear medicine and optical imaging and image-guided intervention. MRI gives the conservative treatment that does not require incision into the body or the removal of tissue of imaging the cervical spine Magnetic Resonance Imaging (MRI) is a medical imaging technology that uses radio waves and a magnetic field to create detailed images of organs and tissues. The impact of the medical image in various fields are constantly growing. Magnetic Resonance Imaging, is an advanced, state-of-the-art radiology method that produces very clear images of the human body without the use of X-rays. MRI has proven to be highly effective in diagnosing a number of conditions by showing the difference between normal and diseased soft tissues of the body. MRI a powerful diagnostic tool in the assessment of both anatomical deformity and tissue pathology. MRI has tremendous potential in the diagnosis of both intraspinal and osteo-articular disease of the cervical spine. MRI gives extremely clear, detailed images of soft-tissue structures that other imaging techniques cannot achieve. MRI has much greater soft tissue contrast than Computed Tomography, making it useful in neurological, musculoskeletal, cardiovascular, and gynecological imaging. This paper presents the survey of various thresholding techniques used in medical imaging.

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Automatic thresholding of gray-level pictures using two-dimension Otsu method

Cited by 116 publications

References 1 publication

Silhouette-based gait recognition using Procrustes shape analysis and elliptic Fourier descriptors

Silhouette-based gait recognition using Procrustes shape analysis and elliptic Fourier descriptors

Instantaneous and ensemble average cavitation structures in Diesel micro-channel flow orifices

Segmentation by Thresholding on Medical Imaging – A Survey

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