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Monitoring of rock fragmentation is a commercially important problem for the mining industry. Existing analysis methods either resort to physically sieving rock samples, or using image analysis software. The currently available software systems for this problem typically work with 2D images and often require a significant amount of time by skilled human operators, particularly to accurately delineate...
Stereo matching, as many problems in computer vision, has been addressed by a multitude of algorithms, each with its own strengths and weaknesses. Instead of following the conventional approach and trying to tune or enhance one of the algorithms so that it dominates the competition, we resign to the idea that a truly optimal algorithm may not be discovered soon and take a different approach. We present...
This paper deals with the problem of recovering the unknown norm of relative translations between cameras based on the knowledge of relative rotations and translation directions. We provide theoretical conditions for the solvability of such a problem, and we propose a two-stage method to solve it. First, a cycle basis for the epipolar graph is computed, then all the scaling factors are recovered simultaneously...
This paper proposes a feature-based technique to detect pedestrians and recognize vehicles within thermal images that have been captured during nighttime. The proposed technique applies the support vector machine (SVM) classifier on CENsus Transformed histogRam Oriented Gradient (CENTROG) features in order to classify and detect humans and/or vehicles. Although thermal images suffer from low image...
Undesirable emails (spam) are increasingly becoming a big problem nowadays, not only for users, but also for Internet service providers. Therefore, the design of new algorithms detecting the spam is currently one of the research hot-topics. We define two requirements and use them simultaneously. The first requirement is a low rate of falsely detected emails which has an impact on the algorithm performance...
We present newly added modules for our autonomous load handling system. The stereo camera system provides information about the scene in front of the automated forklift. A new alternative module for pallet detection is described. Several processing modules for unloading operations are also presented. Our system is evaluated by means of detection rate and by performing field tests. The tests show that...
We present a parallel hierarchical graph clustering algorithm that uses modularity as clustering criteria to effectively extract community structures in large graphs of different types. In order to process a large complex graph (whose vertex number and edge number are around 1 billion), we design our algorithm based on the Louvain method by investigating graph partitioning and distribution schemes...
Previous polarimetric synthetic aperture radar (PolSAR) images change detection methods are generally undertaken in the pixel scale, resulting in overlooking the semantic information. To solve this problem, this paper presents a superpixel-based PolSAR images change detection methods. Different from some previous methods, an improved SLIC superpixel segmentation method is introduced in polarimetric...
In this paper, we propose a new framework for remote sensing images classification based on group sparse representations. It is well known that it is very difficult to find a suitable sparse representation for remote sensing images because of complicated ground features. Here a remote sensing image is deemed a combination of sub-images of smooth, edges and point like components. Since each domain...
Precision size measurements are widely used in industrial production such as candies and cookies in the food industry. However, it is a challenge to measure irregular objects in a universal device because of poor adaptability and low precision. In this paper, a high-precision measurement device for irregular objects based on machine vision is designed. It consists of a rotational adjustment platform,...
By using online measurement and inspection, the efficiency of production in product manufacturing can be greatly improved. However, most of the available methods for the measurement and inspection of parts are offline in practice, which results in either time consuming or expensive inefficiencies. In this paper, a vision-based inspection approach is proposed, which is designed to measure and inspect...
Road damage detection from high-resolution remote sensing image is critical for natural disaster investigation and disaster relief. In a disaster context, the pair of pre-disaster and post-disaster road data for change detection are difficult to obtain due to the mismatch of different data sources, especially for rural areas where the pre-disaster data (i.e. remote sensing imagery or vector map) are...
This paper presents a feature guided multi-window area-based matching method for urban remote sensing stereo pairs. The method achieves the goal that producing dense disparity maps for urban remote sensing stereo pairs. The proposed method can be divided into four stages: feature-based matching, edge support region extraction, area-based matching and post-processing. The point feature matching is...
Scale-space corner detection (SSCD) has been drawing much attention in the past. Multi-scale corner detection (MSCD), which recognizes corners only at several scales, can be treated as a fast implementation of SSCD. In this paper, a new MSCD algorithm is proposed, which is based on an arithmetic mean (AM) of the k-cosine curvature values respectively computed at three scales. Compared to the existing...
One of the key requirements for the evaluation of indoor localization systems is an accurate and reliable ground truth. Existing ground truth systems are often expensive due to high hardware cost and complex deployment. In this work, we present a simple yet highly accurate approach for a cost-effective ground truth system based on off-the-shelf infrastructure cameras and printable markers. We developed...
In many agricultural applications, PolSAR data are widely used because they can be decomposed into various scattering components, which can be of help in observing the characteristics of agricultural areas. Recently, studies have been conducted to find suitable polarimetric parameters for specific applications. This paper tried to find appropriate polarimetric parameters for line extraction from agricultural...
Image registration for stack-based HDR photography is challenging. If not properly accounted for, camera motion and scene changes result in artifacts in the composite image. Unfortunately, existing methods to address this problem are either accurate, but too slow for mobile devices, or fast, but prone to failing. We propose a method that fills this void: our approach is extremely fast—under 700ms...
Large amounts of available training data and increasing computing power have led to the recent success of deep convolutional neural networks (CNN) on a large number of applications. In this paper, we propose an effective semantic pixel labelling using CNN features, hand-crafted features and Conditional Random Fields (CRFs). Both CNN and hand-crafted features are applied to dense image patches to produce...
The use of sweat pores in fingerprint recognition is becoming increasingly popular, mostly because of the wide availability of pores, which provides complementary information for matching distorted or incomplete images. In this work we present a fully automatic pore-based fingerprint recognition framework that combines both pores and ridges to measure the similarity of two images. To obtain the ridge...
We present a graph matching refinement framework that improves the performance of a given graph matching algorithm. Our method synergistically uses the inherent structure information embedded globally in the active association graph, and locally on each individual graph. The combination of such information reveals how consistent each candidate match is with its global and local contexts. In doing...
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