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Formation control of a collection of vehicles is a topic that has generated a lot of interest in the research community. This interest primarily stems from the increased performance and robustness that is provided by a swarm of agents as compared to an individual member. Formation control can be achieved through many approaches. The approach used by this paper is based on a leader-follower premise...
In this paper, we address the problem of impulsive noise reduction in color images through an evolutionary approach. We designed a new hybrid genetic algorithm, called GARIN, which takes as input a noisy image and generates as output a reduced noise version of the same image. As part of its evolutionary process, GARIN integrates the execution of robust and adaptive filters from literature with the...
For image matting, the affinity-based algorithms adore the hierarchical propagation to handle the memory problem. But they rely heavily on the accuracy of the pre-segmentation, and the hard input constrains may lead to the detail missing or foreground error. In this paper, we present a random walk based hierarchical algorithm with extended Dirichlet function. Regarding constrains as regularization,...
Roadside vegetation classification has recently attracted increasing attention, due to its significance in applications such as vegetation growth management and fire hazard identification. Existing studies primarily focus on learning visible feature based classifiers or invisible feature based thresholds, which often suffer from a generalization problem to new data. This paper proposes an approach...
The premise and foundation of autonomous landing relative navigation based on vision for unmanned aerial vehicle (UAV) are accurate detection of landing cooperative target. In order to overcome the problem of cooperative target detection susceptible to illumination change and the interference, a new landing cooperative target detection algorithm based on low rank matrix recovery theory is proposed...
In this paper, we propose a vision-based traffic light and arrow detection algorithm for intelligent vehicles. We detect all three traffic light colours along with the arrow direction robustly for varying illuminations and traffic lights. A fine-tuned convolutional neural network is used in an offline phase to localise the traffic light region-of-interest within a given camera image. Given the constrained...
Moving shadow detection is an important task in computer vision, with applications several fields, such as surveillance, video conference, visual tracking and object recognition. In this paper, we present a Spatio-Temporal based Moving Shadow Detection (STMSD) method, The main idea is: according to the gradient change of current image, we utilize the watershed algorithm to achieve adaptive segmentation...
Real-time human detection in crowded and dynamic environments poses a significant challenge, due to complex background, occlusion and different human poses. In this paper, we propose a two-staged approach using color and depth data taken by an RGB-D camera. The first stage is to find plausible head-top locations quickly in depth image. The second stage is to extract effective discrimination features...
A robust algorithm that detects text from natural scene images and extracts them regardless of the orientation is proposed. All existing methods are designed to operate under a certain constraint, like detecting text only in one direction. Maximally Stable Extremal Regions (MSER) detector is chosen to extract binary regions since it has proven to be robust to lighting conditions. An enhancement technique...
Hashing learning has attracted increasing attention these years with the explosive increase of data. The hashing learning can be divided into two steps. Firstly, obtain the low dimensional representation of the original data. Secondly, quantize the real number vector of the low dimensional representation of each data point and map them to binary codes. Most of the existing methods measure the original...
In this paper, we propose a simple and effective luminance weight prior for single image dehazing. This prior is based on the observation that the atmospheric airlight closely relates to luminance of haze-free image. Plenty of statistical experiments validates that, at each pixel, the normalized luminance of input image can represent the portion of global atmospheric light that reaches the camera...
In this paper we present a technique for identifying the presence of stagnant water bodies in images taken in various settings. Stagnant water bodies, such as puddles, can become sites for mosquitos to grow, which increases the likelihood of the spread of diseases, such as Zika [1]. We observe that existing techniques perform poorly on images of variable quality, variable backgrounds, and focus. We...
Due to the advancement of digital media, data authentication and security has become a major issue. Digital watermarking comes as a solution to it. This paper gives comparative study of digital watermarking technology based on DWT and SVD on various color spaces. The same technique is applied on various color spaces like RGB, YUV and YCbCr in case of color image. The quality of watermarked image is...
Object trackers can be broadly classified into two types — feature based and color based. The feature based trackers are scale and illumination invariant whereas color trackers are better at handling occlusions and long term object detection. In this paper we propose a hybrid tracker that uses a feature based Circulant Structure tracker and a color based Mean Shift tracker running in parallel, that...
To aid an automatic taxiing system for unmanned aircraft, this paper presents a colour based method for semantic segmentation and image classification in an aerodrome environment with the intention to use the classification output to aid navigation and collision avoidance. Based on previous work, this machine vision system uses semantic segmentation to interpret the scene. Following an initial superpixel...
This paper proposes an approach for a tracking method robust to the intersection with objects with appearances similar to a target object. The proposed method targets image sequences taken by a moving camera and is based on the particle filter. Tracking methods using color information tend to track mistakenly a background region or an object with color similar to the target object. The method constructs...
Coin segmentation, or separating the coin area from its background, is inevitably the first step in any robust classification method. Yet, the fact that almost every research relies exclusively on grayscale images taken in controlled environments, with uniform illumination and backgrounds, wastes a vast asset of images commonly taken by numismatists, sellers and collectors. Admittedly, very often...
Depth Image Based Rendering (DIBR) is a technology which converts two dimensional images to three dimension using colour image and its associated depth image. The performance of any DIBR system depends on the perfection of the depth image. Holes/disocclusion will occur in the virtual views generated if the depth map is not perfect. Since holes occur in the virtual views when the intensity changes...
Watermarking is effective method to hide the confidential information into some multimedia at sending side and later extracted at the receiver side to fulfill various requirements. Several algorithms have been proposed by many scholars for embedding watermark in spatial as well as frequency domain. Frequency domain embedding algorithms are more robust against attacks hence, researcher proposed to...
Due to the wide variety of copy videos, the existing video copy detection methods using single feature face great challenges, especially for video content matching, which are difficult to deal with various copy video transformations. To overcome this problem, a video copy detection method based on sparse representation of MPEG-2 spatial and temporal features is proposed in this paper. Firstly, the...
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