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This paper proposes an information hiding method based on block-segmentation strategy. The proposed scheme divides a grayscale image into several 4 times 4 blocks and further segment each block into four small blocks sized 2 times 2. Each small block chooses one reference point to be proceeded with outer embedding process. The chosen points then formed an inner block to be proceeded with inner embedding...
Existing methods for the registration of blurred images are efficient for the artificially blurred images or a planar registration. They are not suitable for image mosaic of the source images from a real camera with an almost fixed optical center. We propose a registration method so that a distortion-free registration on naturally captured images can be obtained. It adopts a multi-resolution and robust...
This paper presents experiments of an approach based on Ncut to recognize object in brain MR images which are relevant with each other. The approach can consider the features in the 3D space through reconstruction weight matrix while using normalized cut. The eigenvectors of the weight matrix show segmentation of the images, and the object is recognized. In contrast with the original, the improved...
Neural networks are relatively successful in recognizing individual patterns. However, when images consist of combination of patterns, a preprocessing step of segmentation is required to avoid combinatorial explosion of the training phase. In practical applications, segmentation is a context dependent task which itself requires recognition. In this paper we propose and develop a biologically inspired...
This paper describes a detection system of traffic sign for use in moving cars. Input image captured from color CCD camera is converted in HSV or RGB color space. In color space are done preprocessing actions, to determine the position of traffic signs. Image segment from this position is further tested for class of traffic sign, which means: features are extracted and used as input in to image classification...
In this paper, we present a new approach for segmentation of tubular structures in 2D images providing minimal interaction. The main objective is to extract centerlines and boundaries of the vessels at the same time. The first step is to represent the trajectory of the vessel not as a 2D curve but to go up a dimension and represent the entire vessel as a 3D curve, where each point represents a 2D...
In this paper, we propose a framework for unsupervised analysis of human behavior based on manifold learning. First, a pairwise human posture distance matrix is calculated from a training action sequence. Then, the isometric feature mapping (Isomap) algorithm is applied to construct a low-dimensional structure from the distance matrix. The data points in the Isomap space are consequently represented...
Methods for detecting weft knitting fabric defects are studied in this article. A new method to analyze the texture information on the fabric image with multi-window for enhancing the defects feature is introduced. The feature information of defect is segmented by cellular neural network and three terms of variables are defined to represent the feature. Using interlock fabric with the defects of hole,...
Driver face monitoring system is a real-time system that can detect driver fatigue and driver distraction using machine vision approaches. In this paper, a new algorithm is proposed for driver hypo-vigilance detection based on eye-region processing and without explicit eye detection stage. In this method, horizontal projection of top half-segment of facial image is used to extract symptoms of fatigue...
This paper focuses on a new iris identification method based on a local analysis of the iris texture. In the method, the iris is divided in sub-regions, using locally sliding windows, to extract local signatures. Local distances are then calculated and fused, based on a weighting average. The sliding allows to compensate for local distortions due to segmentation imprecision. The applied weights take...
In this paper we explore four distinct approaches to extracting regions of interest (ROI) from still images. We show the results obtained for each of the proposed approaches, and we demonstrate where each method outperforms the other. The four approaches are: (1) a block-based discrete wavelet transform (DWT) algorithm, (2) a color saliency approach, (3) a wavelet coefficients variance saliency approach,...
In times of disaster acquiring aerial images is challenging. The unmanned aircraft vehicle (UAV) is a low cost vehicle which can be carried close to the disaster site and flown to capture aerial images without any delay. This paper presents some techniques for UAV image mosaicing from a series of overlapped snapshot images. The process can be divided into three steps. The first step is to detect the...
Thresholding is one of the old, simple, and popular techniques for image segmentation, and has been widely studied. In this paper, an approach for image thresholding based on cellular neural network (CNN) combined with fuzzy c-means (FCM) is presented. The approach realized by threshold CNN (T-CNN), which threshold is obtained automatically via FCM clustering algorithm. Experimental results on real...
In this paper, a segment extraction algorithm based on polygonal approximation for on-line Chinese characters recognition (OLCCR) is presented. With this method, the point with the smallest interior angle is detected and the whole stroke is split into two adjacent curves by this point, which is called as a cut-off point or an inflexion. To each of the two curves, the same step is performed to detect...
In this paper, a generic motion-based approach to semantic video analysis is presented. The examined video is initially segmented into shots and for every resulting shot appropriate motion features are extracted at fixed time intervals. Then, hidden Markov models (HMMs) are employed for performing the association of each shot with one of the semantic classes that are of interest in any given domain...
We propose algorithms to extract groups of meaningful image level lines using Helmholtz perception principle. In this paper, the meaningfulness refers to the segmentation of circular and rectangular shapes in an image. We propose an objective assessment of meaningfulness of an image level line when the level line takes the shape of circle or rectangular segment. We have shown that a logical threshold...
Locating the car license plate in an image a car is an important step in car license plate recognition/identification applications. This problem poses many challenges like location of license plate from images taken in poor illumination and bad weather condition; plates that are partly obscured by dirt and images that have low contrast. This paper presents a morphology based method for license plate...
Most of the thresholding procedures involved setting of boundaries based on grey values or intensities of image pixels. In this paper, the thresholding is to be done based on color values in images of Ziehl-Neelsen sputum slides. The color thresholding technique is being carried out based on the adaptation and slight modification of the grey level thresholding algorithm. Multilevel thresholding has...
This paper proposes a data driven image segmentation algorithm, based on decomposing the target output (ground truth). Classical pixel labeling methods utilize machine learning algorithms that induce a mapping from pixel features to individual pixel labels. In contrast we propose to first extract features from both images and labels. Subsequently we induce a mapping from pixel features to label features...
In this paper we propose a novel and efficient technique for finding keywords typed by the user in digitised machine-printed historical documents using the dynamic time warping (DTW) algorithm. The method uses word portions located at the beginning and end of each segmented word of the processed documents and try to estimate the position of the first and last characters in order to reduce the list...
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