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Shape-specific points are special data points invariant to translation, scaling, and rotation. The radius weighted mean (RWM) and the system center are two examples of shape-specific points. These points feature in contour registration, color quantization, and the detection of rotationally symmetric shape orientations. This study uses shape-specific points to cluster nonlinearly separable data into...
We present an innovative method for detecting interest points (IPs) in grayscale and color images. It is based on the use of angular signatures (ASs), produced by spinning, at each pixel in the image, an "x-tapered, y-derivative, half-Gaussian kernel" in discrete angular steps. By exploiting the AS(s) produced at each pixel, it automatically "classifies" the pixel as being an IP...
Hashing learning has attracted increasing attention these years with the explosive increase of data. The hashing learning can be divided into two steps. Firstly, obtain the low dimensional representation of the original data. Secondly, quantize the real number vector of the low dimensional representation of each data point and map them to binary codes. Most of the existing methods measure the original...
The goal of this paper is to address how to use human experience to develop an enhanced matting strategy. Based on a recursive α optimization framework, we present an adaptive fuzzy learning strategy for enhancement of matting. Taking into account the uncertainty of data, the proposed scheme successfully applies the expert human knowledge into matting. Experimental results are given to demonstrate...
Foreground Detection is one of the critical parts in the field of Computer Vision that aims to identify changes in the image sequences and to separate the foreground image from their background image. It is an arrangement of systems that typically examine the video sequences progressively and are recorded with a stationary camera. To detect brain tissue at early stage, a robotized framework utilizing...
This paper presents an application of machine learning approach for automatic terrain classification suitable for optimal wireless sensor network performance in on-demand deployment. The work entails practical terrain image processing using supervised SVM kernel algorithm moving from gray scale level to color and covering every aspect of a typical terrain image. This paper showcases the integral part...
Single image super resolution requires approximation of high frequency information that was not captured in the available low resolution image. The process may result in an image that differs significantly from the original scene if no constraints are imposed. Iterative back-projection is one method used to guide the resolution enhancement process. This paper augments the iterative back-projection...
In the recent history, kernel methods had established themselves as powerful tools for computer vision. In this paper we introduce an integer image kernel function based on Ramanujan Sums which finds its place in image vision. The paper proves the validity of kernel function theoretically and also shows the application of the kernel in image vision. Ramanujan Sums are based on number theory and hence...
In the study on sports image classification, the characteristics of human pose increasingly raise concerns of researchers. However, the same posture for human may be resulted from different scenes and scene objects that express diverse action states and meanings. Thus, combination of human pose and event scenes shall be considered so as to improve performance of sports image classification. In recent...
This paper proposes guided-colorization-based image coding that utilizes a guide image for encoding chroma components. Up to now, several colorization-based image coding techniques have been proposed. In those techniques, the luma component is encoded by a standard encoder, while the two chroma components by colorization. Namely, the encoder selects representative chroma samples and the decoder recovers...
The chemical burn is one of the major accidents and life treating process in the modern world. The proposed research attempts to find an automated solution for classifying chemical skin burn as superficial, partial thickness and full thickness.. The design and development of such a classifier is clinically very significant particularly, when it is used in remote areas and under emergencies. Towards...
Person identification is an important but still challenging problem in video surveillance. This work designs a completely automatic appearance-based person identification system, which has the ability to achieve new person discovery and classification. The proposed system consists of three modules: background and silhouette separation; feature extraction and selection; and online person identification...
Support Vector Machine (SVM) is widely recognized as a potent data mining technique for solving supervised learning problems. The technique has practical applications in many domains such as e-commerce product classification. However, data sets of large sizes in this application domain often present a negative repercussion for SVM coverage because its training complexity is highly dependent on input...
Social behavior and many cultural etiquettes are influenced by gender. There are numerous potential applications of automatic face gender recognition such as human-computer interaction systems, content based image search, video surveillance and more. The immense increase of images that are uploaded online has fostered the construction of large labeled datasets. Recently, impressive progress has been...
The localization of eye corner is of great importance since it offers crucial information in various face-related applications including face tracking, gaze estimation, and facial expression recognition. In this paper, a new approach is proposed which localizes eye corners in a precise and robust way. In our approach, we first estimate a rough location about an eye corner. Then, a set of texture images...
Food recognition is an emerging computer vision topic. The problem is characterized by the absence of rigid structure of the food and by the large intra-class variations. Existing approaches tackle the problem by designing ad-hoc feature representations based on a priori knowledge of the problem. Differently from these, we propose a committee-based recognition system that chooses the optimal features...
A salient region is the most distinctive part of the image that captures human's attention. Saliency detection is a fundamental characteristic of the human visual system. Finding computational models which are able to detect salient regions is a challenging task for image processing and computer vision applications. Salient regions of various sizes can be detected from different scales. Therefore,...
Focal plane ambiguity in depth map creation from defocus blur has remained an challenging problem. In this paper, we present a method to resolve this issue with the help of Chromatic Aberration(CA). CA is a distortion referred to focal length variation of the lens with wavelength of light. When light, a mixture of various monochromatic components, passes through a lens, multiple focal planes are generated...
Edit propagation is a class of algorithms that propagates user-specified color adjustments across an image or video. The user-specified adjustments take the form of sparse paint strokes that give examples of the desired alterations. Existing edit propagation (EP) algorithms are based on color similarity, and thus will alter all objects that have a similar color. In this work, we describe an EP algorithm...
This paper presents a novel object tracking algorithm. Object appearance and spatial information is learned from a single template using a non-linear subspace projection. A probabilistic search strategy, based on particle filter, is employed to find object region in each frame of the video sequence that best models the target object in the subspace representation. Particle filter estimates the posterior...
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