39,841 research outputs found
Image Segmentation using Rough Set based Fuzzy K-Means Algorithm
Image segmentation is critical for many computer vision and information retrieval systems and has received significant attention from industry and academia over last three decades Despite notable advances in the area there is no standard technique for selecting a segmentation algorithm to use in a particular application nor even is there an agreed upon means of comparing the performance of one method with another This paper explores Rough-Fuzzy K-means RFKM algorithm a new intelligent technique used to discover data dependencies data reduction approximate set classification and rule induction from image databases Rough sets offer an effective approach of managing uncertainties and also used for image segmentation feature identification dimensionality reduction and pattern classification The proposed algorithm is based on a modified K-means clustering using rough set theory RFKM for image segmentation which is further divided into two parts Primarily the cluster centers are determined and then in the next phase they are reduced using Rough set theory RST K-means clustering algorithm is then applied on the reduced and optimized set of cluster centers with the purpose of segmentation of the images The existing clustering algorithms require initialization of cluster centers whereas the proposed scheme does not require any such prior information to partition the exact regions Experimental results show that the proposed method perform well and improve the segmentation results in the vague areas of the imag
Gabor Filter and Rough Clustering Based Edge Detection
This paper introduces an efficient edge detection method based on Gabor
filter and rough clustering. The input image is smoothed by Gabor function, and
the concept of rough clustering is used to focus on edge detection with soft
computational approach. Hysteresis thresholding is used to get the actual
output, i.e. edges of the input image. To show the effectiveness, the proposed
technique is compared with some other edge detection methods.Comment: Proc. IEEE Conf. #30853, International Conference on Human Computer
Interactions (ICHCI'13), Chennai, India, 23-24 Aug., 201
View subspaces for indexing and retrieval of 3D models
View-based indexing schemes for 3D object retrieval are gaining popularity
since they provide good retrieval results. These schemes are coherent with the
theory that humans recognize objects based on their 2D appearances. The
viewbased techniques also allow users to search with various queries such as
binary images, range images and even 2D sketches. The previous view-based
techniques use classical 2D shape descriptors such as Fourier invariants,
Zernike moments, Scale Invariant Feature Transform-based local features and 2D
Digital Fourier Transform coefficients. These methods describe each object
independent of others. In this work, we explore data driven subspace models,
such as Principal Component Analysis, Independent Component Analysis and
Nonnegative Matrix Factorization to describe the shape information of the
views. We treat the depth images obtained from various points of the view
sphere as 2D intensity images and train a subspace to extract the inherent
structure of the views within a database. We also show the benefit of
categorizing shapes according to their eigenvalue spread. Both the shape
categorization and data-driven feature set conjectures are tested on the PSB
database and compared with the competitor view-based 3D shape retrieval
algorithmsComment: Three-Dimensional Image Processing (3DIP) and Applications
(Proceedings Volume) Proceedings of SPIE Volume: 7526 Editor(s): Atilla M.
Baskurt ISBN: 9780819479198 Date: 2 February 201
Detection of nano scale thin films with polarized neutron reflectometry at the presence of smooth and rough interfaces
By knowing the phase and modules of the reflection coefficient in neutron
reflectometry problems, a unique result for the scattering length density (SLD)
of a thin film can be determined which will lead to the exact determination of
type and thickness of the film. In the past decade, several methods have been
worked out to resolve the phase problem such as dwell time method, reference
layer method and variation of surroundings, among which the reference method
and variation of surroundings by using a magnetic substrate and polarized
neutrons is of the most applicability. All of these methods are based on the
solution of Schrodinger equation for a discontinuous and step-like potential at
each interface. As in real sample there are some smearing and roughness at
boundaries, consideration of smoothness and roughness of interfaces would
affect the final output result. In this paper, we have investigated the effects
of smoothness of interfaces on determination of the phase of reflection as well
as the retrieval process of the SLD, by using a smooth varying function (Eckart
potential). The effects of roughness of interfaces on the same parameters, have
also been investigated by random variation of the interface around it mean
position
- …