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Agricultural textures are in the interest of classification in image processing. Natural images have unique textural shapes inside which cause a tough problem for classification. This paper tests different feature extraction and classification approaches to serve a benchmarking on several agricultural databases like seeds and leaves. Features are obtained using Local Binary Pattern (LBP), Gray Level...
This paper proposes a method that separates the region of each leaf from an image of occluded leaves and produces a set of single-leaf images as an output. To identify the region of a single leaf, intersection points and direction field are required. An intersection point, which is defined as a concave point between leaves, is used as the starting position of leaf estimation process. Direction field,...
One of the time consuming tasks in the timber industry is the manually measurement of features of wood stacks. Such features include, but are not limited to, the number of the logs in a stack, their diameters distribution, and their volumes. Computer vision techniques have recently been used for solving this real-world industrial application. Such techniques are facing many challenges as the task...
Recent advances in text detection allow for finnding text regions in natural scenes rather accurately. Global features in content based image retrieval, however, typically do not cover such a high level information. While characteristics of text regions may be reflected by texture or color properties, the respective pixels are not treated in a different way. In this contribution we investigate the...
In this paper an efficient crop row detection method is proposed for vision-based navigation for agriculture robots. In the proposed method, no low level features (such as edges and middle lines of the images) are needed. So the complex algorithms for edging and matching (e.g. the Hough transform) are avoided, which greatly saves the computation loads. Instead, a flexible quadrangle is defined to...
Traffic light is one of the important signs for drivers that help managing the car flow and reducing accident on the road. As of today technology, there exists a traffic light detection system that warns the driver to reduce the accident significantly. In this paper, we are concerned with only the red and yellow traffic light to reduce false positive and time consumption. The fast radial symmetry...
Optical Flow is a very important topic in computer vision, with applications in object tracking, motion estimation and video compression. Recently, Tao et al. proposed the Simple-Flow algorithm - a non-iterative method whose running times increase sublinearly with the number of pixels. SimpleFlow does not use global optimization and uses only local evidence, achieving significant speedups in parallel...
Illumination and color invariance are important problems in computer vision (CV). The Census transform (CT) can resist change of illumination intensity and is widely used for many applications in CV and consumer electronics. However, only grayscale images can be processed in the CT algorithm. In this paper, a new color Census transform (CCT) based on a color invariance model for stereo matching is...
In this paper, we propose a hybrid approach for accurate depth acquisition by using a structured light-based method with a stereo matching. By projecting additional light patterns onto a scene, a structured light-based method works well on a textureless region where a stereo matching shows poor performance. In contrast, the patterns projected onto a rich textured region obstruct in estimating reliable...
The mission of intelligent vehicles is to assist the driver in decision making. The researchers have paid attention on developing various driver assistance systems in order to assure road safety. Most of the driver assistance systems do not produce accurate results in poor weather conditions. Poor visibility is considered to be a main reason for accidents. When the weather is poor (haze, fog, darkness,...
In this paper we present a new vision-based method to measure corn plant spacing and population at early growth stage. Images were acquired from a top-mounted camera under dayLight condition. Algorithms were developed to mosaic image sequence, vegetation segmentation, image thinning, stem center identification, row Line fitting, plant count and plant spacing measurement. Compared the results of vision-based...
Scene classification from images is a challenging problem in computer vision due to its significant variability of scale, illumination, and view. Recently, Latent Dirichlet Allocation (LDA) model has grown popular in computer vision field, especially in scene labeling and classification. However, the effectiveness of the LDA model for the scene classification has not yet been addressed thoroughly...
Rank and census transforms provide high resistance to radiometric distortion, vignette, and noise because they are based on the relative ordering of local pixel intensity values rather than the pixel values themselves. These transforms are widely used in many computer vision applications. An important step of computing these transforms is to compare or rank two grayscale values, which is very much...
This paper uses the open source computer vision library (OpenCV for short) as basic library and calls library functions to achieve real-time video capture and output. We narrate the process of making the matrix interpretable as an image through analyzing the data structure of IplImage and meaning of its member variable. The library functions to read video take the video frame for unit and the storage...
Color transfer is a process of carrying over image colors from one image to another. Since images have diverse texture, color, content and other features, key challenge for color transfer is to find a correct mapping between image and target image. In this paper, a new color transfer method based on feature points extraction and local binary patterns(LBP) mapping is proposed. We construct a framework...
In this paper, we propose a simple but effective method for visibility restoration from a single image. The main advantage of the proposed algorithm is no user interaction is needed, this allows our algorithm to be applied for practical applications, such as surveillance, intelligent vehicle, etc. Another advantage compared with others is its speed, since the cost of obtaining transmission map is...
Horizon detection is a pre-cursor to vision processing in air and water robotics. This paper makes three contributions to horizon detection. First, a theoretical framework for generating pseudo spectra images (PSI), from spectrum analysis of XYZ color-space is presented. Second, wavelengths in the visible spectrum are identified, at which the PSI has similar intensities for sky and clouds. Generating...
People have a growing interest for driver assistant systems that are used to monitor the driving conditions by visual technique, and warn and guide drivers the road conditions. This paper proposes a real-time lane detection algorithm which is a necessary part for driver assistant system and unmanned vehicle. The algorithm presented in this paper integrates multiple cues, including bar filter which...
In the RoboCup competition, vision system is regarded as of great importance with its high information contents, convenient implementation, and suitability for human sights of common and inexpensive hardware. In this paper, we discuss the vision system of ROBOCUP Small Size League, and introduce a digital way for segmentation of this color based robotic motion, camera calibration is also included...
Geometric rearrangement of images includes operations such as image retargeting, inpainting, or object rearrangement. Each such operation can be characterized by a shiftmap: the relative shift of every pixel in the output image from its source in an input image. We describe a new representation of these operations as an optimal graph labeling, where the shift-map represents the selected label for...
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