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A new spatial domain steganography method for the grayscale image is presented in this paper. The method has used neighboring pixel pair difference value and Least Significant Bit (LSB) substitution, which provides enhanced embedding capacity. This method uses a 3×3 block structure to divide the cover image into some non-overlapping blocks horizontally. k-LSBs of the center pixel of the cover image...
Image intensity inhomogeneity and low contrast aretwo substantial challengesfor image segmentation. In this work, we propose a new active contour method forsegmenting images with inhomogeneous intensity and low contrast. To deal with the intensity inhomogeneity, we use a local image fitting term. To deal with low contrast, we use a strictly convex and differential function as the data fidelity measure...
Hand gesture plays an important role in nonverbal communication and natural human-computer interaction. However, the complex hand gesture structure and various environment factors lead to low recognition rate. For instance, hand gesture depends on individuals, and different individuals' hands are with different sizes and postures, in addition, unconstrained environmental illumination also influences...
Existing image steganographic methods lack in the complexity, which can be utilized by the radical to decode the images and neutralize the operations. Several methods have been proposed in order to combat this. Perhaps the most efficient method is Block-based Edge Adaptive based on Least-Significant-bit Matched Revisited (LSBMR) approach. It is a famous type of steganographic methods in the spatial...
The traditional random sample consensus (RANSAC) algorithm is capable of estimating a model with fewer data points and almost unaffected by noise. There are several drawbacks of such algorithm including detection errors, unstable threshold and massive calculation. By analyzing the spatial relations of graphics pixels, a hypothetical circle is firstly formed with three hypothetical points which are...
Pose estimation and 3D environment reconstruction are crucial for autonomous navigation in mobile robotics. Robust dense visual odometry based on a RGB-D sensor uses all pixels to estimate frame-to-frame motion by minimizing the photometric and geometric error. 3D coordinates of each pixel are calculated necessarily with its corresponding depth. However, depths of some pixels near object boundaries...
An intuitive approach is proposed for outlier recognition among 2D point correspondences. The main novelty of the proposed method is the exploitation of feature point topology provided by Delaunay triangulation. The solution obtained by minimizing an energy originated from neighboring correspondences in order to remove incorrectly paired points. Assuming local, approximately rigid structures, it is...
At present, due to advancement in communication technology and internet, people are sharing images over social networking and other sites very efficiently but it has created problems regarding copyright protection and authentication of the images. In past 10–15 years, digital watermarking has been becoming a popular solution for these problems. Besides of being popular, it creates distortions in host...
This paper proposes and evaluates an algorithm to automatically detect the cataracts from color images. Currently, methods available for cataract detection are based on the use of either fundus camera or DSLR camera; both are very expensive. The main motive behind this work is to develop an inexpensive, robust and convenient algorithm which in conjugation with suitable devices will be able to diagnose...
Text data present in scene images may be the important clue for indexing, automatic footnote, and indexing of images. Now-a-days extraction of text from images has become one of the fastest growing research areas in the field of computer vision. In scene images, text data are present with huge variations in font sizes, styles, alignments, and orientations. These variations make the task of detection...
In this paper, we propose a new approach for dense disparity estimation in a global energy minimization framework. We combine the feature matching cost defined using the learned hierarchical features of given left and right stereo images, with the pixel-based intensity matching cost to form the data term. The features are learned in an unsupervised way using the deep deconvolutional network. Our regularization...
In this paper, we address the problem of visual tracking in videos without using a pre-learned model of the object. This type of model-free tracking is a hard problem because of limited information about the object, abrupt object motion, and shape deformation. We propose to integrate an object-agnostic prior, called objectness, which is designed to measure the likelihood of a given location to contain...
The complexity of Balinese script and the poor quality of palm leaf manuscripts provide a new challenge for testing and evaluation of robustness of feature extraction methods for character recognition. With the aim of finding the combination of feature extraction methods for character recognition of Balinese script, we present, in this paper, our experimental study on feature extraction methods for...
Relational data arising in many domains can be represented by networks (or graphs) with nodes capturing entities and edges representing relationships between these entities. Community detection in networks has become one of the most important problems having a broad range of applications. Until recently, the vast majority of papers have focused on discovering community structures in a single network...
The goal of this article is to analyze the assurance of permissible quality indices in an interval system through the construction of the edge route and the use of D-partition method. There were obtained conditions for construction of D-partition domains on one and two edges of one face. On the basis of these conditions the technique for assurance of the permissible degree of robust stability and...
Text detection in natural scenes holds great importance in the field of research and still remains a challenge because of size, various fonts, line orientation, different illumination conditions, weak character and complex background in image. The contribution of the proposed method is filtering out complex backgrounds by utilizing two masks filtering based on text confidence map in the first step...
This paper presents a study on the exploitation of visual information from two points of view radically different. Computer vision is a branch of artificial intelligence that focuses on the extraction of useful information in an image. Image matching is a fundamental aspect of many problems in computer vision. Several algorithms have been developed for this purpose. Based on this research, this paper...
Human action recognition in video sequences is an important research topic in computer vision, and motion history image (MHI) is widely taken for recognition due to its simplicity. However, it may be not robust to describe an action by only a single MHI. Therefore, an action recognition scheme by using multiple key MHIs (MKMHIs) is proposed. Firstly, an adaptive method for key MHIs selection is proposed...
The linear sampling method is known to be a simple and computationally efficient approach to retrieve the support of the scatterer using multistatic scattered field data. However, the recovered profile is always misleading, owing to the lack of robust edge detecting. This paper addresses this open issue. Using moving least square approximation, the upper and lower bounds of the profile of scatterers...
In this paper we present a new lane markers detection and estimation algorithm aiming to improve lane detection methods. We first estimate the area of lane marking using the profile of the lane estimation in a confidence map. After that a fitting method is applied to improve the lane marker detection accuracy. To track our lane markers over time and make the association between two iteration, we use...
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