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In this thesis, four typical algorithms for image feature extraction are studied first, by analyzing their advantages and disadvantages and according to the actual needs of the project, SIFT algorithm is selected to be the foundation of the research. By analyzing the disadvantages of SIFT and its relational improved model, based on the two way guiding and matching strategy, have proposed a new matching...
This paper presents a novel approach, named bag-of-bags of words (BBoW), to address the problem of Content-Based Image Retrieval (CBIR) from image databases. The proposed bag-of-bags of words model extends the classical bag-of-words (BoW) model. An image is represented as a connected graph of local features on a regular grid. Then irregular partitions (subgraphs) of images are further built via Normalized...
Online social networks have found a significant increase in their popularity in recent years. All the networks have community structure, and one of the research problems mostly frequently tackled is the discovery of communities. An overlapping community is a network structure that allows one node to be a member of multiple communities. The method presented in this paper aims at detecting overlapping...
Horizon line detection has several important applications in airborne and marine navigation as well as in surveillance and tracking. Many methods for horizon line detection use only the intensity component of still images and video sequences discarding the color information. Other algorithms locate the horizon line in color images using the information of all the color components. In this work we...
Automatic segmentation of organs at risk in head Magnetic Resonance Images (MRI) is a challenging task it necessitates accurate definition of organs at risk (OAR). This crucial step is time consuming and prone to inter and intra-observer variations. Automatic segmentation by atlas deformable registration may help to reduce time and variations. the atlas based segmentation of brain OAR may suffer from...
A new method for image sharpening via image warping is proposed. The idea of the method is to warp the uniform grid of the image in a way that the pixels around the blurred edge move closer to the edge according to its blurriness. The advantage of the proposed method is that instead of an accurate estimation of the blur kernel only approximate value of the edge blur level is required. Also, since...
Image Retrieval is a system which extracts the relevant set of images and matches with query image from large collection of dataset. It is used in variety of domains including finger print identification, biodiversity information system, digital library, medical imaging etc. An effective and efficient system is required to improve its retrieval performance. In CBIR, the images are indexed according...
This paper are presented novel method of texture segmentation using active contour model incorporated with edge flow. The edge flow magnitude was used as a main force (external force) of active contour model. The texture segmentation from both active contour model with edge flow and traditional active contour model were compared. The results reveal that the active contour models with edge flow shown...
In this paper, a low-complexity and high-efficiency scheme is developed for frame rate up conversion (FRUC). Texture based adaptive motion estimation is carried out for improving the accuracy of motion vectors. In addition, the proposed scheme comprises a motion vector post-processing method which corrects the outliers in nine directions. Moreover, in order to deal with the artifacts caused by the...
This paper presents a novel neural network based patch reordering approach for image denoising and expression. This technique is grounded on estimating the correct location of the patch pixels corrupted by noise using neural network and median filter. The presented work relates the pixel value at the center of the patch with each pixel in the patch window and then estimates the correct location for...
The quantum advancement seems, by all accounts, to be a dominating technology around the most ensuring advancements for building a future figuring schema. A quick comes about of the norms of quantum material science is the colossal enlisting energy of quantum machine compared to that of a made one. This is the result of three astonishing quantum assets that have no conventional accomplices: Quantum...
In this paper we consider the problem of matching feature points between multi-source images. Straightforwardly comparing visual features such as SIFT may result in desirable local feature correspondences for single-source images. However, when it comes to matching feature between multi-source images, e.g. between an RGB color image and an infrared image, the feature based matching scheme tends to...
In this paper we propose a full automatic segmentation of the knee cartilage from magnetic resonance images (MRI). The new segmentation approach is based on a combination of the Vector Field Convolution (VFC) image's features and radial search algorithm. The proposed approach provides an automatic segmentation and a 3D visualization of the knee cartilage.
Edge detection is an elementary step used in various image processing applications. The main problems in existing edge detection algorithms are poor edge localization, less noise removal capacity, unable to detect edges in complex background images and inability to properly detect the color edges in images. In this paper a sequential hybrid approach is proposed to overcome all the limitations of existing...
Noise is inherent in digital systems. To smooth a point cloud while preserving sharp edges, a new 3D bilateral filter is proposed. It uses the point cloud normal vector in addition to color as a position vector for preserving sharp edges while smoothing the color. The bilateral blurs data while preserving strong edges. In 2D images, the concept of edge is defined by an abrupt change in color. In this...
Feature extraction is a process of detecting and extracting features out of images and storing it in feature vectors. It is an important phase of content based image retrieval. Extracted features are equally significant in terms of their usage since they can be further taken as inputs to next phases of CBIR. There are several techniques used for extracting features out of an image. In this paper we...
Video shot boundary detection is the process of automatically detecting the meaningful boundary in video data. It becomes an essential pre-processing step to video analysis, summarisation and other content-based retrieval. Video frame feature representation also plays an important role in the process where it directly affects to the performance of the system. Histogram dissimilarity-based with the...
In this paper, a novel single image super-resolution technique based on neighbor embedding is proposed. Conventional neighbor embedding technique uses gradient feature vector in neighbor selection. However, since gradient feature is high-frequency feature, it is not appropriate for feature representation in weak-edge and texture regions. Therefore, instead of using only gradient feature as in neighbor...
Community detection is one of the most important problems in social network analysis in the context of the structure of the underlying graphs. Many researchers have proposed their own methods for discovering dense regions in social networks. Such methods are only designed with links of the underlying social network. However, with the development of recent applications, rich edge content can be available...
Robust and efficient detection of cars in urban scenes has many useful applications. This paper introduces a framework for car detection from high-resolution satellite images, wherein a novel extended image descriptor is used to depict the geometric, spectral and colour distribution properties of cars. The proposed framework is based on a sliding-window detection approach and it begins with a pre-prepossessing...
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