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A new image segmentation method is proposed to combine the edge information with the feature-space method, K-Means clustering. A procedure called seam processing, which is computationally efficient, is employed to search for horizontal and vertical seams that contain edge information. By transforming the spatial coordinates based on the seam detection results, the edge information can be added to...
We present an intelligent approach for understanding user interaction to simplify the interface of graph-based image segmentation. The user draws a set of markers (strokes) over the object and the background, and our method automatically determines a subset of these pixels with dissimilar image properties for arc-weight estimation. Arc-weight estimation combines object information learned from the...
This paper intends to propose a novel clustering method based on ant colony (AC) algorithm. A new approach called TT-transform based time frequency analysis is used in processing the non-stationary power signal disturbances. The time-time transform is the inverse Fourier transform of S-transform. The proposed model is demonstrated using feature vector from the domain of power signal analysis, yielding...
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...
The purpose of this article is to present a novel algorithm for ship wake detection in synthetic aperture radar (SAR) images. The main originality of our work is that splitting the image with small window before conventional Radon transform to make the illumination has stronger consistency in each window and adopting clustering algorithm to select real wakes form disturbing lines. Experimental result...
High-precision localization is one of the important applications in the field of computer vision. In this paper a high-precision template localization algorithm based on SIFT (scale invariant feature transform) is presented. The proposed method is composed of three main steps. In the initial step the SIFT features are extracted. With these features the basic matching strategy and clustering method...
The paper discusses insect footprint recognition. Footprint segments are extracted from scanned footprints, and appropriate features are calculated for those segments (or cluster of segments) in order to discriminate species of insects. The selection or identification of such features is crucial for this classification process. This paper proposes methods for automatic footprint segmentation and feature...
With the growing number of digital multimedia libraries, the need to efficiently index multimedia information is increasing, detecting and extracting the text information from images plays an important part in images indexing based on content. In the paper, a new text extraction algorithm under background image based on two-dimensional wavelet transforms is proposed. For the algorithm, firstly the...
Image segmentation is the first step towards image analysis and image understanding. However, most image segmentation algorithms require a priori knowledge of the number of partitions in the image to be segmented. This paper introduces a novel method for completely unsupervised image segmentation by using wavelet analysis and fuzzy Gustafson-Kessel (GK) algorithm. The proposed algorithm needs no predefined...
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