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Segmentation in echo-cardiographic images is a difficult task due to the presence of speckle noise, low contrast and blurring. We present a novel method based on clustering performed in the feature space. A new feature-based image representation is proposed. It is obtained by computing a local feature descriptor at every pixel location. This descriptor is derived using the Radon-Transform to effectively...
Wireless Capsule Endoscopy (WCE) is a state-of-the-art technology to examine the entire gastrointestinal tract. Its main disadvantage is long review time for physicians to diagnose diseases, as it will produce over 55,000 frames per patient for one examination. In this paper we propose a novel strategy to segment WCE video clips based on abnormality. The new scheme is based on a non-parametric corner...
Research on footwear impression evidence has been gaining increasing importance in forensic science. Given a footwear impression at a crime scene, a key task is to find the closest match in a local/national database so as to determine footwear brand and model. This process is made faster if database prints are grouped into clusters of similar patterns. We describe a clustering approach based on common...
This paper presents an innovative approach for localizing and segmenting duplicate objects for industrial applications. The working conditions are challenging, with complex heavily-occluded objects, arranged at random in the scene. To account for high flexibility and processing speed, this approach exploits SIFT keypoint extraction and mean shift clustering to efficiently partition the correspondences...
This paper proposes an efficient approach for object classification. This method bases on bag-of-features classification framework and extends the limits of it. It applies modified spatial PACT as local feature descriptor, which can efficiently catch image patch's characteristic. In order to address the speed bottleneck of codebook creation, extremely randomized clustering forest is used to create...
Micrographs of Chinese wines show floccule, stick and granule of variant shape and size. Different wines have variant microstructure and micrographs. A semisupervised wine classification method based on kernel principal component analysis (KPCA) method and fuzzy C-means (FCM) algorithm using edge feature from micrographs was proposed in this paper. In this work, ten Chinese wines are determined or...
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