Results 311 to 320 of about 501,901 (323)
Some of the next articles are maybe not open access.
2006
In this chapter, a robust algorithm for segmenting food imagery from a background is presented using colour images. The proposed method has three steps: (i) computation of a high contrast grey value image from an optimal linear combination of the RGB colour components; (ii) estimation of a global threshold using a statistical approach; and (iii) a ...
Mery Quiroz, Domingo Arturo +1 more
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In this chapter, a robust algorithm for segmenting food imagery from a background is presented using colour images. The proposed method has three steps: (i) computation of a high contrast grey value image from an optimal linear combination of the RGB colour components; (ii) estimation of a global threshold using a statistical approach; and (iii) a ...
Mery Quiroz, Domingo Arturo +1 more
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Image segmentation in thermal images
2016 IEEE International Conference on Industrial Technology (ICIT), 2016This paper presents a novel method for image segmenting in thermal images. A thermal imaging sensor is a device that forms an image by detecting the infrared radiation from objects in a scene and comparing their temperature differences. In this study, we characterized an object's heat signature (its mean temperature and variance) by segmenting its ...
Yung-Yao Chen +2 more
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2011
This chapter introduces image segment techniques. These techniques, including pixel- based approaches, region-based approaches, classification techniques, deformable model algorithms, artificial neural network approaches and texture-based algorithms are detailed. Color image segmentations and 3D image segment methods are briefly introduced.
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This chapter introduces image segment techniques. These techniques, including pixel- based approaches, region-based approaches, classification techniques, deformable model algorithms, artificial neural network approaches and texture-based algorithms are detailed. Color image segmentations and 3D image segment methods are briefly introduced.
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Image segmentation and image models
Proceedings of the IEEE, 1979This paper discusses image segmentation techniques from the standpoint of the assumptions that an image should satisfy in order for a particular technique to be applicable to it. These assumptions, which are often not stated explicitly, can be regarded as (perhaps informal) "models" for classes of images.
Larry S. Davis, Azriel Rosenfeld
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Image segmentation in pyramids
Computer Graphics and Image Processing, 1982Abstract A method of image segmentation was recently introduced based on defining links between pixels at adjacent levels of a “pyramid” of reduced-resolution versions of the image. This paper studies some of the problems that arise with linked-pyramid segmentation, and proposes a two-stage segmentation process that overcomes these problems.
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Unsupervised segmentation of color images
Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269), 2002A novel technique for unsupervised learning in feature space is presented. The feature space is considered as composed of two distinct sources, “mode” and “valley”, in the point of view of information theory. An entropy-based thresholding is taken to distinguish the discretized cells in the feature space. The cells labeled as “mode” are then chained to
Guo, Guodong, Yu, Shan, Ma, Songde
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Image-Measurement Segmentation
Journal of Marketing Research, 1978Product positioning studies for both new and established products generally involve consumers’ perception of the current product space in terms of the salient product attributes. Perceptions per brand attribute are hypothesized to be a function of direct measurement and brand “image.” The influences of direct measurement and image are separated.
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Image Segmentation by Image Analogies
2014In this paper we propose a new technique for image segmentation based on contour detection using image analogies principle. A set of artificial patterns are used to locate contours of any query image. Each pattern allow the location of contours corresponding to specific intensity variation.
Asma Bellili, Slimane Larabi
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Image segmentation or image understanding ?
ICASSP '82. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005In Image processing, it is often implicitely admitted that an image is known when it has been segmented in various textures, in accordance with the judgement of the human eye. Two counter examples are presented, in biology and in petrology, showing that image analysis may also consist in synthetizing informations disseminated over a large number of ...
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2010
Image segmentation is a fundamental part in low level computer vision processing. It has an essential influence on the subsequent higher level visual scene interpretation for a wide range of applications. Unsupervised image segmentation is an ill-defined problem and thus cannot be optimally solved in general.
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Image segmentation is a fundamental part in low level computer vision processing. It has an essential influence on the subsequent higher level visual scene interpretation for a wide range of applications. Unsupervised image segmentation is an ill-defined problem and thus cannot be optimally solved in general.
openaire +2 more sources