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This manuscript addresses the cross-spectral stereo correspondence problem. It proposes the usage of a dense flow field based representation instead of the original cross-spectral images, which have a low correlation. In this way, working in the flow field space, classical cost functions can be used as similarity measures. Preliminary experimental results on urban environments have been obtained showing...
In this paper, a Binary Robust Invariant Scalable Keypoints (BRISK) based detection is utilized to facilitate the flying unmanned aerial vehicle (UAV) localization within its autonomous landing on the runway. Specifically, two target detection algorithms are proposed and developed as the BRISK-supported approach. Dataset of images and differential GPS are recorded by a ground stereo vision guidance...
A new region-based local stereo matching algorithm with accurate disparity estimation is proposed. For the local stereo matching, finding an appropriate support window is crucial to the performance of disparity estimation. In order to generate an accurate support region, a modified cross-based local approach combined with mean-shift segmentation is performed. We then further improve the reliability...
Almost every computer vision applications used background subtraction method to detect moving objects from video sequence. Moving object detection and tracking is generally the first step in many applications such as face detection, traffic surveillance, object recognition, detection of unattended bags, people counting etc. Background modeling is very useful and effective method for locating objects...
Over the last decade, feature point descriptors such as SIFT have become indispensable tools in the computer vision community. But, the descriptor's high computational overhead becomes a significant concern when it has to be on a device with limited computational and storage resources. In order to make descriptors faster to compute and more compact, several binary descriptors such as ORB and BRISK...
The need for fast retrieving images has recently increased tremendously in many application areas. SIFT-like local descriptor-based matching is widely adopted and has achieved state-of-the-art performance. However, it becomes inefficient when computational and storage resources are limited. Besides, local descriptor-based methods may suffer difficulties when an image pair contains multiple similar...
This paper presents a novel shadow detection method in remote sensing images based on edge feature description of candidate regions. Edge gradient ratio is defined and used to represent the inherent properties of shadow regions. To improve the detection result, weighted edge gradient ratio (WEGR) is addressed, where the weight of a region is determined by the number of pixels belonging to shadow in...
Computer vision systems are being introduced in pre-screening of cervical cytopathology slides to identify samples that require study by cytopathologists. These systems work on the principle of imaging and analysis of cytology features in general and nuclear features in particular. Thus accurate localization and segmentation of the nuclei is crucial for the systems. Though several methods have been...
This paper implements four interpolation methods to modify the adaptive support weight (ASW) algorithm in multiresolution image representation. The disparity values at lower resolution level are used to determine disparity values of undetermined pixels at higher level during the interpolation procedure. The first interpolation method fills an undetermined pixel (a gap) with the averaged disparities...
The amber gemstones classification system is proposed and described in this paper. The amber data used in experiments are collected by amber art craft industry experts and divided manually into 30 classes. The presented investigations were care out in order to find out most accurate and fast classifier for online amber sorting application. QDA, KNN, RBF, and decision tree classifiers were tested....
Human action recognition is the process of labeling videos contain human motion with action classes. The run time complexity is one of the most important challenges in action recognition. In this paper, we address this problem using video abstraction techniques including key-frame extraction and video skimming. At first we extract key-frames and then skim the video clip by concatenating excerpts around...
Scene decomposition into its illuminant, shading, and reflectance intrinsic images is an essential step for scene understanding. Collecting intrinsic image groundtruth data is a laborious task. The assumptions on which the ground-truth procedures are based limit their application to simple scenes with a single object taken in the absence of indirect lighting and interreflections. We investigate synthetic...
Date fruits are small fruits that are abundant and popular in the Middle East, and have growing international presence. There are many different types of dates, each with different features. Sorting of dates is a key process in the date industry, and can be a tedious job. In this paper, we present a method for automatic classification of date fruits based on computer vision and pattern recognition...
In this paper, we design, evaluate and compare two phase-based passive stereovision architectures. We present two approaches to implement phase-based correspondence search algorithms in real-time for sparse stereovision applications. The first approach enhances the accuracy of the 1D phase correlation method. The second approach optimizes the 2D phase correlation method at the cost of degradation...
Superpixel segmentation has become a popular preprocessing step in computer vision with a great variety of existing algorithms. Almost all algorithms claim to compute compact superpixels, but no one showed how to measure compactness and no one investigated the implications. In this paper, we propose a novel metric to measure superpixel compactness. With this metric, we show that there is a trade-off...
This paper presents a comparative study of different classification methodologies for the task of fine-art genre classification. 2-level comparative study is performed for this classification problem. 1st level reviews the performance of discriminative vs. generative models while 2nd level touches the features aspect of the paintings and compares semantic-level features vs low-level and intermediate...
Efficient location of fruits in the trees is the most important criterion of an automatic robotic harvesting system. The main challenges faced in the development of the robotic harvesting arm are accurate identification of the fruits in dense foliages and detection of the occluded fruits. This paper proposes a statistical technique that accurately detects and tracks pomegranates in trees. A k-means...
The usual method for classification processes of brazil-nut is manual and present some drawbacks like slowness, subjectivity, and inconsistency. In this paper, the main objective is to automate the classification process by analysing digital images with multiple brazil-nuts. These images have been segmented using the Level Set method without reinitialization with a new stopping criteria based on the...
It attracts many researchers' attention to find a stereo matching algorithm both accurate and fast. Yoon and Kweon's Adaptive Support-Weight(ASW) method is supposed to be a very successful algorithm in both accuracy and speed. However, it is very time consuming for ASW to take a large number of pixels into consideration for computing a disparity. In this paper, we present a stereo matching algorithm...
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