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Image completion is to recover its damaged regions to get a visually satisfactory result. Recently, exemplar-based method is an important method, which propagates sample patches into unknown regions from known regions. It should take two steps. The first is to search for the most matching patch in another same intact image, or the other part of this image, and the second is to inpaint the damaged...
On the base of FCM arithmetic which is in existence, in order to get the preferable separating effect, we bring forward an adaptive algorithm for the weight of the feature weighted of FCM which founds on the feature contribution balance principle and the most separate degree principle of intra-cluster. The arithmetic avoids each feature of the feature data originated can't be compared non-comparatives...
In this paper, we present a visual system to drive an autonomous small-scale helicopter to track a ground target. The vision system is monocular, and the on-board camera is fixed. Since the time-varying attitude of helicopter can bring trouble to vision algorithm design, we developed an attitude compensation algorithm. The real flight experiments show that the vision system can perform in real-time,...
To against the complexity in finding feature-pair in image registration caused by traditional features: corners, lines and image edge, a novel method for image registration based on rectangle pattern is proposed. Unlike traditional features, a rectangle pattern can be described as its four vertexes and center, which can afford five pair-wise points for any kind of image transformation, and it holds...
Orthogonal experimental design, an effective method of multi-factors researches, is capable of reducing the times of experiments, determining the sequence of priority of influencing factors rapidly and figuring out the best parameters and confidence degree. The novel characteristic of this paper is to apply the orthogonal experimental design into the evaluation research of image processing algorithms...
In this paper, we propose Semi-Supervised pLSA(SSpLSA) for image classification. Compared with the classic non-supervised pLSA, our method overcomes the shortcoming of poor classification performance when the features of two categories are quite similar. By introducing category label information into EM algorithm, the iteration process can be directed carefully to the desired result. SS-pLSA greatly...
In this paper, we propose a novel unsupervised clustering method for feature space analysis. We combine mean shift with a transductive learning method, semi-supervised discriminant analysis (SDA), in an incremental learning scheme. We use mean shift clustering to generate the class label, and use SDA to do subspace selection. Both these steps are performed alternately. Our clustering result could...
Auto-focus technology is the core part of the automatic optical measure system. Auto-focusing algorithm based on image processing is a long-standing topic in the literatures. The focus-evaluation-function is mathematical description used to measure whether the image is focused or not. The existing sharpness functions will work well for still image sometimes, but in optical tracking measure system,...
Fingerprint images are textural images consisting of ridges and valleys. The orientation of textures can be determined by orientation field computation. Fingerprint orientation field is the critical basis for fingerprint image segmentation, filtering enhancement and matching processes, and the fingerprint orientation field algorithm plays a very important role in the applied Automated Fingerprint...
The Scanning Electronic Microscopy (SEM) images are usually used to analyze a certain kind of material properties. To get automatic and accurate quantitative research, image processing methods are utilized to analyze surface morphology from the images obtained from SEM. In this paper, we focus on the Activated Carbon Fiber (ACF) SEM material images. K-nearest neighbor smoothing and Lapalacian sharpenning...
This paper proposed a general image segmentation model, namely the energy-minimization based image segmentation (EMBIS) model. This model converts image segmentation into a controlled optimization process minimizing the weighted sum of the feature energy and spatial energy, which interpret the homogeneity restriction and spatial constraints, respectively. The EMBIS model provides a unified understanding...
This paper proposes an efficient approach to find clusters of spatially related scene images collected from the website. Our method firstly builds a guide table, in which the ranked results are given according to the relevance scores of image pairs obtained by the image retrieval methods. Then the image clusters are generated by repeatedly choosing a seed image and performing query expansion directed...
Based on image content, a new watermarking robust algorithm were presented in this paper. A region formed by feature points of the image is used to embed mark. The feature points and region eliminate the effect of geometric distortion, Experiments demonstrate that the technique can well withstand attacks such as rotating, scaling and JPEG lossy compression.
The paper presents an adaptive image deblurring method with ringing control. Images are split in analogy with unsharp mask into low- and high-frequency components. Edges are sharpened in low-frequency domain using deconvolution with Total Variation constraint. High-frequency information is amplified using ringing level control.
Reconstruction speed and image quality are the keys of 3D image reconstruction in cone beam CT (CBCT), this article have researched on the 3D image reconstruction in CBCT, and a self-adapting fast reconstruction method for high resolution images is presented. The method is based on the FDK algorithm and Z-line data first algorithm, which introduces the reconstruction task division algorithm based...
Through simulating the process of image degradation, a new model for image enhancement is proposed in this paper, the new model has explained and realized the theory of Color constancy, here it is called DPSM (degradation process simulation model). Then an algorithm based on DPSM to do image enhancement is proposed, an illumination image removal process and a contrast upgrading process are included...
SENSC algorithm is a newly proposed stable and efficient NSC algorithm. In this paper the SENSC algorithm is evaluated for the task of image clustering. A series of experiments are conducted on two different kinds of image datasets, including face images and natural images, and SENSC is compared with some other commonly used clustering methods. Experimental results show that SENSC is better suited...
Edge detection is a fundamental operation in video and image processing. For real time processing, hardware implementation of edge detection becomes necessary. This study designs an edge detection IP (Intellectual Property) core, to be readily used by other applications that need such functionality. The core is very fast and produces good detection quality. The paper also suggests that more research...
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