Image Segmentation using Morphological Operations

Chudasama, Diya; Patel, Tanvi; Joshi, Shubham; Prajapati, Ghanshyam I.

doi:10.5120/20654-3197

Cited by 59 publications

(32 citation statements)

References 7 publications

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“…Specifically, dilation and erosion were operated to enlarge and shrink the target phase by pushing or pulling the voxels at the phase boundary using a structure element (SE). The algorithms of these morphological operations can be found here 37,38 . To obtain a graded-particle volume, the original particles were firstly eroded by approx.…”

Section: Discussionmentioning

confidence: 99%

“…6a), here we obtain the graded-particle structure (Fig. 6b) by morphological erosion 37,38 of the initial particles in a region within 12 μm of the separator/electrode interface and filling the gap between particles with small ones so as to maintain the same active material volume fraction (see Methods for more details). The decrease of particle size benefits the electrochemical performance by increasing the number of interfacial reaction sites (Fig.…”

Section: D Characterisation Of Microstructural Heterogeneitiesmentioning

confidence: 99%

“…The electrode electrochemical performance is closely related to mass transport capability, especially close to the separator for high C-rates. To investigate this, morphological dilation 37,38 of the local pore structure (see Methods for more details) was conducted to enlarge the pore size by 250 nm at three distances away from the separator to obtain graded-pore structures (R1, R2 and R3 in Fig. 7a−c).…”

Section: D Characterisation Of Microstructural Heterogeneitiesmentioning

confidence: 99%

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3D microstructure design of lithium-ion battery electrodes assisted by X-ray nano-computed tomography and modelling

et al. 2020

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Driving range and fast charge capability of electric vehicles are heavily dependent on the 3D microstructure of lithium-ion batteries (LiBs) and substantial fundamental research is required to optimise electrode design for specific operating conditions. Here we have developed a full microstructure-resolved 3D model using a novel X-ray nano-computed tomography (CT) dual-scan superimposition technique that captures features of the carbonbinder domain. This elucidates how LiB performance is markedly affected by microstructural heterogeneities, particularly under high rate conditions. The elongated shape and wide size distribution of the active particles not only affect the lithium-ion transport but also lead to a heterogeneous current distribution and non-uniform lithiation between particles and along the through-thickness direction. Building on these insights, we propose and compare potential graded-microstructure designs for next-generation battery electrodes. To guide manufacturing of electrode architectures, in-situ X-ray CT is shown to reliably reveal the porosity and tortuosity changes with incremental calendering steps.

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Section: Discussionmentioning

confidence: 99%

Section: D Characterisation Of Microstructural Heterogeneitiesmentioning

confidence: 99%

Section: D Characterisation Of Microstructural Heterogeneitiesmentioning

confidence: 99%

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3D microstructure design of lithium-ion battery electrodes assisted by X-ray nano-computed tomography and modelling

et al. 2020

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“…At this stage, regions that alter along both axes are highlighted with white colour. Next, morphological opening [15][15] is used to enhance the results, and both of the images overlap. Then morphological closure takes place, and contours of white zones are located and filtered by area, relative to the minimum possible area of the defect.…”

Section: Defect Detectionmentioning

confidence: 99%

Real-time system for automatic cold strip surface defect detection

Kostenetskiy¹,

Alkapov²,

Vetoshkin³

et al. 2019

FME Transactions

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Detection and classification of surface defects of the rolled metal are one of the main tasks for correctly assessing product quality. Historically, these tasks were performed by a human. However, due to a multitude of production factors, such as high rolling rate and temperature of the metal, the results of such human work are rather low. Replacing a human controller with an artificial intelligence system has been relevant for a long time; it is merely necessary within the concept of Industry 4.0. This paper is devoted to the development of the prototype system automatic detection and classification of defects for one of the Iron-and-Steel Works of the Chelyabinsk region in the Russian Federation. The prototype consists of the Preprocessor, Classifier, Server, Database, and User interface. The main focus is on achieving high classification accuracy, which is planned to be obtained through the use of convolutional neural networks.

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“…The morphological closing operation is achieved by applying dilation and erosion operation using the same structural element. According to [23], while dilation adds pixels to the boundaries of objects in an image, erosion removes pixels on object boundaries. After the successful completion of the stage, the face finding stage was carried out.…”

Section: Morphological Operationsmentioning

confidence: 99%

Development of a Face Detection Algorithm Based on Skin Segmentation and Facial Feature Extraction

Popoola¹,

Akinola²

2017

International Journal of Engineering Technologies IJET

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This paper presents a face detection algorithm capable of detecting face(s) without prior training as a face classifier. The technique employed in developing the algorithm is based on skin segmentation and facial feature extraction of the two eyes and mouth. Skin segmentation was done in the red, green, blue color space. White balance correction was employed to correct the change in image temperature that occurs due to change in lighting conditions at the point of acquiring image. Morphological operations and bounding box were employed to search and extract face region from the segmented skin region. Facial feature, eyes and mouth, were extracted for final verification of the sensed face using the Laplacian of Gaussian filter and the isosceles triangle matching rules. The extracted features were used to develop the face detection algorithm. The developed algorithm was evaluated using random images taken under different lighting conditions. Furthermore, the efficiency of the developed face detection algorithm was evaluated using a standard face detection image database. The result obtained shows that the developed face detection algorithm performed satisfactorily well with 81.37% detection accuracy. Furthermore, the results obtained from the performance evaluation of the developed face detection for this study has shown it clearly that accuracy detection of dissimilar faces in images with complex background is possible and attainable.

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Image Segmentation using Morphological Operations

Cited by 59 publications

References 7 publications

3D microstructure design of lithium-ion battery electrodes assisted by X-ray nano-computed tomography and modelling

3D microstructure design of lithium-ion battery electrodes assisted by X-ray nano-computed tomography and modelling

Real-time system for automatic cold strip surface defect detection

Development of a Face Detection Algorithm Based on Skin Segmentation and Facial Feature Extraction

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