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Visual saliency detection has become a challenging area in computer vision. In this paper, we propose a novel region based saliency detection model which considers background priors. The proposed method consists of two successive steps — region weighting and contrast computing. In the step of region weighting, we calculate the region weight for each region by region-level image feature and a log-linear...
Calorie measurement systems that run on smart phones allow the user to take a picture of the food and measure the number of calories automatically. In order to identify the food accurately in such systems, image segmentation, which partitions an image into different regions, plays an important role. In this paper, we present the implementation of Graph cut segmentation as a means of improving the...
This paper introduces a multi-class classification algorithm based on sparse representation which considers on rejection option to minimize risks caused by outliers. Here the outliers include signals that do not belong to any classes learned in a training step. To successfully reject the outliers, new rejection measure and corresponding dictionary learning algorithm are presented. Experimental results...
This paper proposes a novel human detection and validation methodology to help the visually impaired navigate in indoor environments. We used two-stage multiscale cascade object detectors with Haar features, to detect upper body parts at different poses. The resulting detections are validated by scaling them down to their annotated size and performing a multiscale window search of possible face poses...
The correspondence problem refers to the problem of ascertaining which parts of one image correspond to which parts of another image. Correspondence problem usually needs to be solved by feature extraction and feature matching first, as a prerequisite for vision-based control and estimation. To avoid this bottleneck, assuming that an object is on a plane or has a planar surface, we present a model...
This paper studies the scale we choose for boundary detection. The common multi-scale method for detecting boundary requires the users to compute several scales of boundary on the whole image, train the coefficients as the weight of each scale's information, and combine the multi-scale boundary using the training weight. It has been proposed that human visual system evolved to be able to change the...
In this paper, we present a novel approach for visual loop-closure detection in autonomous robot navigation. Our method uses locality sensitive hashing (LSH) as the basic technique for matching the binary visual features in the current view of a robot with the visual features in the robot appearance map. We show that this approach is highly efficient in comparison with using non-binary visual features...
A novel approach to robust and flexible person tracking using an algorithm that integrates state of the arts techniques; an Enhanced Person Detector (EPD) and Kalman filtering algorithm. This proposed algorithm employs multiple instances of Kalman Filter with complex assignment constraints using Graphics Processing Unit (GPU-NVDIA CUDA) as a parallel computing environment for tracking multiple persons...
In this paper, one of the peculiar applications of the Boundary Integral — Resonant Mode Expansion (BI-RME) method, namely shape analysis and recognition, is reviewed. We explore the advantages for shape analysis and recognition of a BI-RME based modal matching algorithm, where each shape is represented by means of a set of eigenfunctions, solutions of the Helmotz equation with Dirichlet boundary...
In this paper, we propose a novel inertial-assisted visual odometry system intended for low-cost micro aerial vehicles (MAVs). The system sensor assembly consists of two downward-facing cameras and an inertial measurement unit (IMU) with three-axis accelerometers/gyroscopes. Real-time implementation of the system is enabled by a low-cost embedded system via two important features: firstly, simple...
Iris has a unique pattern that can be used in biometric recognition. To extract the features of the iris, it can be done based on the textural characteristics of the iris pattern. One method is a texture-based feature extraction using wavelet. To construct a wavelet type which matched for a signal, in this case two-dimensional signal from the iris image, the necessary steps are quite complex. In this...
A potential loop-closure image pair passes the geometric verification test if the number of inliers from the computation of the geometric constraint with RANSAC exceed a pre-defined threshold. The choice of the threshold is critical to the success of identifying the correct loop-closure image pairs. However, the value for this threshold often varies for different datasets and is chosen empirically...
It is no doubt that fingerprint recognition is the most common biometric modality, which can be used to authenticate the identity of a person. Automatic identification systems based on fingerprint recognition have been extensively deployed in the industrial and forensics area. The performance of these systems relies on the accuracy of the fingerprint comparison algorithm, which is still suffering...
In this paper, a fast and accurate algorithm to distinguish between open and closed eye is proposed. In the proposed approach, we use a fast and accurate preprocessing stage based on Haar features to detect the face area, color and intensity mapping to extract the eye candidate areas, and some simple geometrical constraints for final approval of the eye area. Then, for detecting the eye state with...
Nowadays, automatic computer-Aided Diagnosis (CAD) systems for grading different types of cancers like breast cancer are very prevalent. These systems employ histopathology slide images acquired by advanced and well-defined digital scanners. The previously proposed automatic or computer-aided systems for breast cancer grading, especially by counting mitoses, suffer from various types of deficiencies...
Feature point tracking is one of the most important subjects in machine vision due to its abundant applications. The advantage of this sort of tracking compared with other tracking methods is in extracting exact position information from tracking object's components. Three important problems in this issue are accuracy, speed and stability of the tracking system subject to illumination variations,...
In this paper, Geodesic Derivative Pattern (GDP) for Off-line handwritten signature verification is presented. We combine features based on both gray level and geometric information in the decision level. The Local Derivative Pattern (LDerivP) and the geodesic distance are used as features. It should be mention that the geodesic distance has never been used in offline signature verification. The method...
Contemporary search engines and other automated web tools are faced with the task of extracting relevant information from huge web archives. This is supposed to be a difficult task due to the semi-structured and unstructured nature of the web documents. Users need automated ways of organizing and cataloging the web documents so that they can be queried efficiently. Clustering is typically employed...
With the increasing development of underwater vision sensors, simultaneous localization and mapping (SLAM) based on stereo vision has become a hot topic in the areas of ocean investigation and exploration. In this paper, visual SLAM with a focus on stereo camera system is presented to estimate the motion of autonomous underwater vehicles (AUVs) and build the feature map of surrounding environment...
Defocusing is used in bright-field image processing in order to increase image contrast. Moreover, defocused images can be used to solve the transport of intensity equation (TIE) and obtain physical light phase. Recently, it was shown that the monogenic local features of an axial intensity derivative passed through a specific low-pass filter can be used to improve cell segmentation. In this paper,...
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