A Novel Approach to Image Segmentation
01 Jan 2013-
TL;DR: This paper is describing a novel approach to image segmentation by performing some steps over the edges detected of all the objects present in the foreground or background to help in digital image watermarking application for more efficient embedding of watermark.
Abstract: In some applications like, image recognition, compression and watermarking it is likely to be inefficient and unpractical to process the whole image. In that case it is necessary to segment the image before recognising, compressing or embedding some watermark. For this several image segmentation approaches are available to segment the image, to change the representation of the image or to simplify the image to make it more meaningful and easy to analyse. Image segmentation is the process of partitioning an image into multiple segments. This paper is describing a novel approach to image segmentation by performing some steps over the edges detected of all the objects present in the foreground or background. Also this approach will be very helpful in digital image watermarking application for more efficient embedding of watermark.
Citations
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01 Jan 2019
TL;DR: This paper reviews segmentation techniques such as theory-based, region- based, thresholding, edge-based," Neural Network-based", Model-based" and Partial differential equation based on the basis of their functioning, utility, advantages, disadvantages, and applications.
Abstract: In this ascension era of technology, Magnetic resonance imaging (MRI) emerges as the utmost clinically acceptable imaging modality for detection and diagnosis of tumors The Breast tumor is leading scrupulous diseases among women In last two decades, image segmentation has got a high boost and attention from the researchers across the globe To represent the image in such a way which is easy to analyze and more meaningful, the process of segmentation is used It is the primal step in processing images of different types Therefore, the image is sectioned into desirable building blocks Basically, it provides the meaningful objects of the image Literature provides a variety of image segmentation algorithms even though there is a requirement of an efficient segmentation technique which can work efficiently on all sorts of images The key extract of an algorithm lies within the superiority of segmentation performed by a particular method The availability of segmentation algorithms is quite large, so the analysis of these algorithms might be interesting to the researchers This paper reviews segmentation techniques such as theory-based, region-based, thresholding, edge-based, Neural Network-based, Model-based, and Partial differential equation based on the basis of their functioning, utility, advantages, disadvantages, and applications
19 citations
01 Jan 2014
TL;DR: The approach to image segmentation by performing direction flow and the ROI is described, which will be very helpful in digital image watermarking application for more efficient embedding of watermark.
Abstract: In fingerprints minutiae can be used as identification marks for fingerprint verification. For minutiae extraction in fingerprints with varying quality this paper uses preprocessing in form of image enhancement and binarization is first applied on fingerprints before they are evaluated. Then Image segmentation is used for the finger print image processing in that case the block direction estimation and ROI is used . Many methods have been combined to build a minutia extractor and a minutia matcher. It is necessary to segment the image before recognizing the finger print images. For this several image segmentation approaches are available to segment the image, to change the representation of the image or to simplify the image to make it more meaningful and easy to analyse. Image segmentation is the process of partitioning an image into multiple segments. This paper is describing the approach to image segmentation by performing direction flow and the ROI. Also this approach will be very helpful in digital image watermarking application for more efficient embedding of watermark.
7 citations
15 Jun 2019
TL;DR: The proposed work utilizes a model that extracted the categorical region by culling the concrete area and marks the vertices, double click at the last vertices utilizing mouse, the area automatically extracted corresponding to the masking that is discretely exhibited.
Abstract: In this world of digitized era there is immense desideratum of image processing which manipulates the image information for analysis purport. Any image can be characterized by its feature sets, which demonstrate the detailed information of the images and enhance their visual interpretation. The features are extracted corresponding to the whole image comprised of both ROI (region of interest) and Non-ROI regions. Additionally, the region of Non-ROI shows promising results for obnubilated information corresponding to expected disease. So, for that purport we have proposed a method that extract the feature from the ROI and the Non-ROI region corresponding to the mark vertices in an image utilizing mouse click. The proposed work utilizes a model that extracted the categorical region by culling the concrete area and marks the vertices, double click at the last vertices utilizing mouse, the area automatically extracted corresponding to the masking that is discretely exhibited. The proposed work uses two neuroimaging modalities such as CT-Scan and MRI. As per the survey of radiologist, Medico and medicos, most of the time they concentrated only those components of the image i.e. ROI that can be facilely detectable and shows the cause of disease. They have to leave the rest of the component of the image i.e. Non-ROI that can be cause of the further detection of disease. In furthermore we extracted the obnubilated consequential information from the unattended portion of the neuroimaging modalities i.e. Non-ROI.
4 citations
19 Mar 2015
TL;DR: This paper deals mainly on the various segmentation techniques available for handwritten script recognition system, an important technique for image processing that helps in optical Character recognition systems (OCR).
Abstract: Different scripts are used for writing purposes. It is very much important to identify/know these scripts before an appropriate character recognition algorithm is chosen. This paper deals mainly on the various segmentation techniques available for handwritten script recognition system. It is an important technique for image processing. Image segmentation provides meaningful objects of the image. Identification of a script in handwritten recognition system is really a challenging task in real world. Many researchers are indulged in the recognition of scripts from handwritten documents over four decades. This task becomes more and more challenging when it comes to multi lingual/script country like India. An input Image is preprocessed through various steps and segmented by different available techniques. This identification of script helps in optical Character Recognition systems (OCR)
3 citations
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...978-1-4799-7075-9/15/$31.00 ©2015 IEEE...
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Journal Article•
TL;DR: Comparison on comparative study of segmentation techniques for segmenting brain tumor from Magnetic Resonance Image is provided.
Abstract: A tumor is an abnormal growth of cells within the brain, which is one of the major causes of death among people . Chances of survival is high if the tumor are detected in the early stages so, there is a need for a fast and accurate method for detection of brain tumor. For detecting the tumor MRI or CT scan is used. Magnetic resonance image is a difficult task because of the location, intensities and shapes. For scanning the image MRI or CT scan is used. Scanning of the brain is done to confirm the presence of tumor and to identify the location. Segmentation is required for brain tumor detection. This is one of the important part in an image processing. It subdivides an image into regions or objects. The main goal of segmentation is to make image easier and meaningful. This paper provides review on comparative study of segmentation techniques for segmenting brain tumor from Magnetic Resonance Image.
2 citations
References
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TL;DR: Attempts have been made to cover both fuzzy and non-fuzzy techniques including color image segmentation and neural network based approaches, which addresses the issue of quantitative evaluation of segmentation results.
3,527 citations
Journal Article•
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TL;DR: How the field of computer (and robot) vision has evolved, particularly over the past 20 years, is described, and its central methodological paradigms are introduced.
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02 Feb 2001
TL;DR: Computer Vision presents the necessary theory and techniques for students and practitioners who will work in fields where significant information must be extracted automatically from images, a useful resource book for professionals and a core text for both undergraduate and beginning graduate computer vision and imaging courses.
Abstract: From the Publisher:
Computer Vision presents the necessary theory and techniques for students and practitioners who will work in fields where significant information must be extracted automatically from images. It will be a useful resource automatically from images. It will be a useful resource book for professionals and a core text for both undergraduate and beginning graduate computer vision and imaging courses.
Features
Topics include image databases an virtual and augmented reality in addition to classical topics.
Offers a complete view of two real-world systems that use computer vision.
Contains applications from industry, medicine, land use, multimedia, and computer graphics.
Includes over 250 exercises and programming projects, 48 separately defined algorithms, and 360 figures.
The companion website features include image archive, sample
1,880 citations
TL;DR: An extensive evaluation of the unsupervised objective evaluation methods that have been proposed in the literature are presented and the advantages and shortcomings of the underlying design mechanisms in these methods are discussed and analyzed.
996 citations
"A Novel Approach to Image Segmentat..." refers methods in this paper
...Region based segmentation: Compared to edge detection method, segmentation algorithms based on region are relatively simple and more immune to noise [5, 11]....
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Proceedings Article•
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TL;DR: An axiomatic definition for the notion of "segmentation" in image processing is proposed, which is based on the idea of a maximal partition and a key theorem links segmentation with connection, on the one hand, and with connective criteria on the other one.
Abstract: Firstly, the paper proposes an axiomatic definition for the notion of "segmentation" in image processing, which is based on the idea of a maximal partition. Then a key theorem links segmentation with connection, on the one hand, and with connective criteria on the other one. A series of lattice properties are then developed. In a last part, two examples of segmentations are proposed.
386 citations