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Retrieving images depend of specific features In Content Based Image Retrieval (CBIR). A common approach is to divide retrieval process into two stages; the first one is based on high-level features followed by the second that is based on low-level features. We focus primarily on medical images, and follow the above approach but make the following two basic contributions: a) introduce the gray cluster...
In recent years, with the explosion of digital images on the Web, content-based retrieval has emerged as a significant research area. Shapes, textures, edges and segments may play a key role in describing the content of an image. Radon and Gabor transforms are both powerful techniques that have been widely studied to extract shape-texture-based information. The combined Radon-Gabor features may be...
In this paper, we discuss some of the key contributions in the current decade related to image retrieval and automated image annotation. General content-based image retrieval (CBIR) also could be improved by the proposed approach in a similar manner as text-based retrieval is improved. In this case no text information is available, but only visual features are used. The CBIR identifies relevant articles...
This paper addresses the problem of automated prosthesis modelling and manufacturing, whose machining parameters are based on images extracted from different medical databases. The specific case of 3D surface restoration of a defective skull was used as study case. A method based on adjusted ellipses on skull bone curvature performs the symbolic representation of searching parameters. The superellipse...
This paper proposes a new descriptor for radiological image retrieval. The proposed approach is based on fuzzy shape contexts, Fourier transforms and Eigenshapes. At first, fuzzy shape context histograms are computed. Then, a 2D FFT is performed on each 2D histogram to achieve rotation invariance. Next, histograms are projected onto a lower dimensionality feature space. The new space is more representative...
The anterior osteophyte (AO) is a bony spur on the vertebra and is symptomatic of osteo-arthritis of the spine. We present advances in our research into matching vertebral boundaries based on pathological (severity) and visual similarity. Proposed image retrieval methods are based on partial shape matching (PSM) that use landmarks along sagittal vertebral outlines that are consistent with those used...
Searching for vertebrae in a large collection of spine X-ray images that are relevant to pathology is potentially important for providing assistance to radiologists and bone morphometrists. Developing appropriate methods for such searching tasks is very challenging due to the high similarities among vertebral shapes in contrast to the subtle dissimilarities that characterize the pathology. In this...
In this paper content based image retrieval of x-ray images using fusion of spectral & shape features is discussed. Texture analysis and shape description are two of the key parts of image content description. Most of the existing descriptors are usually either application dependent or non-robust so we have used spectral measure for content analysis and Fourier descriptors for shape analysis....
In modern day crimes and terrorism, it has become imperative to identify by features the criminals who are involved and who have caused such a disaster. The current work is a basic step towards such an important identification process. In this direction, we begin our work with the identification of fuzzy geometric shapes, which resemble with the actual geometric shapes fuzzily. Zadeh proposed Computing...
Visual understanding is often based on measuring similarity between observations. Learning similarities specific to a certain perception task from a set of examples has been shown advantageous in various computer vision and pattern recognition problems. In many important applications, the data that one needs to compare come from different representations or modalities, and the similarity between such...
Mitosis number of tumor cells is an important factor for pathological examinations. Therefore, to get diagnostic information about tumor cells calculating the number of mitosis cells, first of all, it is photographed tumor cells using light microscopy. Number of mitotic cells determined using image processing methods. Aim of the feature extraction for mitosis cell, entropy value, maximum and minimum...
Content based medical image retrieval (CBMIR) is been highly active research area from past few years . We describes a efficient approach and algorithm that capable of extracting the key information from the medical images based on there shape. We use the Generic Fourier Descriptor (GFD) with Brightness as additional parameter to have good retrieval accuracy. Image is represented in polar form and...
The process of medical image classification is still carried out manually using the knowledge of the physician or radiologist, which leads to inaccurate and slow process of object identification. Thus, we need an automatic system that can classify medical images, accurately and faster from query images into one of the pre-defined classes. In this research, we are dealing with the classification of...
Label-equivalence-based connected-component labeling algorithms complete labeling in two or more raster scans. In the first scan, each object pixel is assigned a provisional label, and label equivalences between provisional labels are recorded. For doing this task, all conventional algorithms use the same mask that consists of four processed neighbor pixels to process every object pixel. This paper...
Feature extraction and selection are two important steps for shape retrieval. Given a data set, a set of features which describe the shape property from different aspects are extracted. Our goal is a learning-based methodology to select the features for improving retrieval performance. Our approach uses both global and local feature descriptors. The global shape features include geometric ones (elongation,...
Medical image features extraction is a crucial part in medical image retrieval system. In order to extract the medical image feature more accurately for improving the retrieval efficiency, a sort of novel feature called rdquofrequency layer featurerdquo and a method used for extracting the feature were proposed in this paper. First, the image was decomposed several sub-images in different frequency...
One of the main challenges for Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings between the high-level semantic concepts and the low-level visual features in images. This paper presents an approach for bridging this semantic gap to improve retrieval quality using the Ranking Support Vector Machine (Ranking SVM) algorithm. Ranking SVM is a supervised learning algorithm which models...
The rapid development of technologies and steadily growing amounts of digital information highlight the need of developing an accessing system. Content-based image indexing and retrieval has been an important research area in computer science for the last few decades. The approaches of content-based image retrieval using low level features such as colour, shape and texture are investigated to create...
Performance of traditional content-based image retrieval systems is far from userpsilas expectation due to the ldquosemantic gaprdquo between low-level visual features and the richness of human semantics. In attempt to reduce the ldquosemantic gaprdquo, this paper introduces a new effective image retrieval approach-the multi-step queries strategy-that facilitates retrieval of semantically similar...
A point of a discrete object is called simple if it can be deleted from this object without altering topology. In this article, we present new characterizations of simple points which hold in dimensions 2, 3 and 4, and which lead to efficient algorithms for detecting such points. In order to prove these characterizations, we establish two confluence properties of the collapse operation which hold...
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