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In order to achieve accurate attitude measurement and smooth navigation controlling of unmanned surface vehicle (USV), a visual horizon tracking method based on Kalman filter has been proposed. Firstly, the approximate parameters of the visual horizon are estimated according to the predictive camera attitude, and the candidate image pixels are obtained in a small region of interest around the predicted...
Image segmentation plays a basic and important role in image processing, and its results are directly related to the ones of image analysis and understanding. Aiming at solving the problem of choosing the optimal threshold-weighted threshold of commonly used thread segmentation methods, this paper proposed the method of integrating genetic algorithm with OTSU method for image segmentation, and adopted...
Skin color segmentation is an important step in vision based Human Computer Interaction (HCI). But, accuracy of the color-based skin detection methods are severely affected by the presence of skin-like colors in the background. In this paper, a skin segmentation method for tackling a specific case of foreground and the background color similarity is proposed. An initial skin mask is obtained by a...
Watermarking has been used extensively for the security of images. The wavelet transform based watermarking has been used for authentication of different images using various techniques. Work presented in current paper proposes a biometric watermarking technique for multimedia (image) data content protection using Gabor feature for extracting the most significant features from the iris image. Lifting...
Object recognition via shape matching has been a fundamental topic in robot vision. More and more technologies are widely used in the field of robot and automation in recent years. The shape contour contains meaningful information for object characterization, therefore, an effective representation of shape contour is important for the capability of a shape matching method. In this work, we propose...
In this paper, we present a motion segmentation based robust multi-target tracking technique for on-road obstacles. Our approach uses depth imaging information, and integrates persistence topology for segmentation and min-max network flow for tracking. To reduce time as well as computational complexity, the max flow problem is solved using a dynamic programming algorithm. We classify the sensor reading...
The paper presents a novel technique to segment and extract streets from satellite images. This technique utilizes, for the first time in the known literature, the Maximally Stable Extremal Regions (MSER) algorithm to robustly identify and segment streets from satellite images. The technique extracts dark MSERs and then classifies them based on multiple metrics such as the intensity of the pixels,...
Knowledge of vertebra location, shape and orientation is crucial in many medical applications such as orthopedics or interventional procedures. The wide range of shapes, joint alterations and pathological cases encountered in an aging population makes automatic segmentation sometimes challenging. This paper presents a new automated vertebra segmentation method for 3D CT data which tackles these problems...
It is crucial to detect the locations of brain tumors for the diagnosis. The aim of this study was the generation and comparison of the high and low-grade probabilistic brain tumor maps to present the tumor observance frequencies in the brain tissue. T1-weighted, pre-operated data from 162 brain tumor patients are examined during the study. Although most of high-grade tumors are located around the...
In case of disasters such as cyclones, earthquakes, severe floods etc., widespread damages to infrastructures such as power grid, communication infrastructure etc. is commonplace. Especially to power grid, the damages to various structures are typically spread out in wide areas. Usage of drones to do fast remote survey of damage area is gaining popularity. From the remote surveillance video of any...
This paper describes an automatic tissue segmentation algorithm for brain MRI of children with cerebral palsy (CP) who exhibit severe cortical malformations. Many of the currently popular brain segmentation techniques rely on registered atlas priors and so generalize poorly to severely injured data sets, because of large discrepancies between the target brain and healthy (or injured) atlases. We propose...
Dense correspondence computation is a critical computer vision task with many applications. The most existing dense correspondence methods consider all the neighbors connected to the center pixels and use local support region. However, such approach might only achieve a locally-optimal solution.In this paper, we propose a non-local dense correspondence computation method by calculating the match cost...
‘Maximally Stable Extremal Regions’ (MSER) based interest points are frequently used for medical image registration on account of their robustness to noise, better localization, and good repeatability. However, if the objects in the image do not have sharp boundaries (as is the case with medical images), the number of MSER's detected is low. Also, MSER's are highly sensitive to image blur. This paper...
Modifying or enhancing an image is ubiquitous but, when enhancement tends to change the interpretation of the image they are termed as an attempt of forgery on digital images. Copy move forgery (CMF) is a simple technique and has a number of well built tools in a number of image enhancement software. CMF detection techniques often tend to establish similarity between copied and pasted region on the...
Hand detection plays an important role in Human Computer Interaction (HCI). Most of the existing hand detection methods rely on the contour shape of hand after skin color segmentation. Such contour shape based approaches, however, are easily distorted by noises and other skin color segments. In this paper, we present a distance image based approach using CPU-GPU heterogeneous computing. Our experiments...
In this paper we present a method to segment RGBD image of a scene into coherent and meaningful parts using both the appearance features and depth information. The segmentation method is totally based on graph cuts theory which uses our proposed unsupervised Conditional Random Field (CRF) model. We evaluate our method both quantitatively and qualitatively on a set of RGBD images of NYU dataset. The...
This work proposes a recognition system for clothing classification by computer vision. The input is an image of the type of fashion catalog where the clothes are fully exposed with models showing their faces. For the preprocessing and features extraction the Bag of Features (BoF) is employed. There are four steps in the proposed classification method: (i) the cloth in an image is identified and located,...
One challenge concerning the reliability of ball grid array (BGA) packages assembly is to detect the void defects occurring inside solder balls. Additionally, for use in mass production, an automated inspection system has increasingly become an attractive solution. In practice, the first procedure of this system is required to segment the individual solder balls from the background. Here, we have...
Obstacle detection is a key technology of intelligent transportation and autonomous robot navigation. Aiming at the shortages of traditional obstacle detection technologies, the paper applies the Kinect depth camera as the sensor of obstacle detection system, and an obstacle detection method based on Kinect depth image is proposed on the theoretical basis of Kinect real-time 3D reconstruction and...
Object recognition is a versatile capability. Automatic guided tours and augmented reality are just two examples. Humans seem to do it subconsciously — unaware of the extensive processing required for it — while it is a complex task for machines. Methods based on SIFT features have proven to be robust for recognition. However, a prior detection step is required to limit confusion, caused by, e.g.,...
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