Results 31 to 40 of about 3,600 (211)
Scaleāadaptive superpixels for medical images
Background Superpixel segmentation is a powerful preprocessing tool to reduce the complexity of image processing. Traditionally, size uniformity is one of the significant features of superpixels. However, in medical images, in which subjects scale varies
Limin Sun, Dongyang Ma, Yuanfeng Zhou
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Optimized method for segmentation of ancient mural images based on superpixel algorithm
High-precision segmentation of ancient mural images is the foundation of their digital virtual restoration. However, the complexity of the color appearance of ancient murals makes it difficult to achieve high-precision segmentation when using traditional
Jinxing Liang +10 more
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Infrared Image Superpixel Segmentation Based on Seed Strategy of Contour Encoding
Superpixel segmentation has become a crucial pre-processing tool to reduce computation in many computer vision applications. In this paper, a superpixel extraction algorithm based on a seed strategy of contour encoding (SSCE) for infrared images is ...
Weihua Li +3 more
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Superpixel segmentation is becoming ubiquitous in computer vision. In practice, an object can either be represented by a number of segments in finer levels of detail or included in a surrounding region at coarser levels of detail, and thus a superpixel segmentation hierarchy is useful for applications that require different levels of image segmentation
Xing Wei 0001 +4 more
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Rooted Spanning Superpixels [PDF]
Abstract This paper proposes a new approach for superpixel segmentation. It is formulated as finding a rooted spanning forest of a graph with respect to some roots and a path-cost function. The underlying graph represents an image, the roots serve as seeds for segmentation, each pixel is connected to one seed via a path, the path-cost
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SUPERPIXEL-BASED UNSUPERVISED CHANGE DETECTION USING MULTI-DIMENSIONAL CHANGE VECTOR ANALYSIS AND SVM-BASED CLASSIFICATION [PDF]
In this paper, a novel superpixel-based approach is introduced for unsupervised change detection using remote sensing images. The proposed approach contains three steps: 1) Superpixel segmentation.
Z. Wu, Z. Hu, Q. Fan
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Tumor localization in tissue microarrays using rotation invariant superpixel pyramids [PDF]
Tumor localization is an important component of histopathology image analysis; it has yet to be reliably automated for breast cancer histopathology. This paper investigates the use of superpixel classification to localize tumor regions.
Akbar, Shazia +7 more
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A Survey of Weakly-supervised Image Semantic Segmentation Based on Image-level Labels
According to the different ways of image-level label location inference, the weakly-supervised image semantic segmentation methods with image-level labels were divided into superpixel-based methods and classification-network-prior based methods.
Xinlin XIE +5 more
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Video Segmentation with Superpixels [PDF]
Due to its importance, video segmentation has regained interest recently. However, there is no common agreement about the necessary ingredients for best performance. This work contributes a thorough analysis of various within- and between-frame affinities suitable for video segmentation.
Fabio Galasso +2 more
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Resolution-Independent Meshes of Superpixels [PDF]
The over-segmentation into superpixels is an important pre-processing step to smartly compress the input size and speed up higher level tasks. A superpixel was traditionally considered as a small cluster of square-based pixels that have similar color ...
Smith, P +3 more
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