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In this paper, we devise a method for introducing affine invariance into the SIFT algorithm considering the addition of affine invariance property to the efficient SIFT algorithm for image matching. An intermediate step of detecting MSER in Comparison of matching performance was performed with reference to original SIFT algorithm. Other deciding factors such as execution time, number of detected interest...
Most commonly used CAPTCHAs are text-based CAPTCHAs which relay on the distortion of texts in the background image. With the development of automated computer vision techniques, which have been designed to remove noise and segment the distorted strings to make characters readable for OCR, traditional text-based CAPTHCAs are not considered safe anymore for authentication. A novel image based CAPTCHA...
Shopping carts have traditionally been used as a tool provided to the customers in retail stores to carry items from the shelf to checkout stations. These days shopping carts can also be used as a security checkpoint to prevent store losses. All the items collected in a shopping cart are supposed to be unloaded at the checkout station to be scanned and included in the bill. Any items left in the cart...
This paper presents a local stereo matching algorithm based on the window construction method using local edge detection. In order to improve performance of window-based cost aggregation computation, a new rule called Dissimilar Intensity Support technique is proposed to distinguish support pixels with dissimilar intensities from those with similar intensity for each centered pixel. According to the...
The video quality can be degraded because of physical problems such as repeated projection, low-quality compression/decompression, or bad chemical decomposition of the original recording material. It becomes increasingly important to locate degraded video (video with defects) with the wide application of digital media. One common video defection is mosaic, where several even square combined together...
Many well-known existing image matching methods are based on local texture analysis, and consequently have difficulty handling low-textured 3D objects, such as those man-made buildings and road networks in urban scenes. In this paper, we propose our urban images matching method utilizing multiple novel clues. Specifically, we explore robust image features generated by interest regions and edge groups...
Feature matching plays an important role in many applications, including 3D reconstruction, object recognition and video understanding. Point matching has made great progress recently, while it has made little progress in the fields of line and curve matching. By computing statistics of point descriptors constructed at each edge points, this paper develops a novel method for extending point descriptors...
Depth information acquisition is one of the key technologies of FTV (Free View Television) system. To obtain accurate depth information, an improved depth estimation method is proposed. For each pixel in the reference view and current view, gradients between current pixel and its eight neighboring pixels as well as the average value of the nine pixels' luminance are computed. To increase depth accuracy...
We consider the problem of image recognition using local features. We present a method for matching Maximally Stable Extremal Regions using edge information and the chamfer distance function. We represent MSERs using the Canny edges of their binary image representation in an affine normalized coordinate frame and find correspondences using chamfer matching. We evaluate the performance of our approach...
In this paper, we describe a prior-based vanishing point estimation method through global perspective structure matching (GPSM). In contrast to the traditional approaches which require an undistorted image with straight roads for vanishing point estimation, our method first infers vanishing point candidates of an input image from an image database with pre-labeled vanishing points. An image-based...
Computer vision involves image edge detection which is crucial in outline capturing systems for decomposing and describing an object. This paper presents a scalable parallel algorithm skeleton for outline capturing and object recognition based on first order difference chain encoding. UNIX based Intel Xeon 2-Quadra-Core system is used for the implementation of the parallel algorithm. The algorithm...
Interest points are widely used in computer vision applications such as camera calibration, robot localization and object tracking that require fast and efficient feature matching. A large number of techniques have been proposed in the literature. This paper evaluates the state of art techniques for interest point detection including execution time and suitability for real time applications. Such...
In this paper, we explore the key factors in the design and implementation of visual computing (image processing and computer vision) algorithms on the massive parallel GPU (graphics processing units). The goal of the exploration is to provide common perspective and guidelines of using GPU for visual computing applications. We have selected three nontrivial applications (multiview stereo matching,...
Pattern matching and image patches correspondence have been described in several papers. However, in most cases the results are obtained using images with high level of detail, in other words, images with useful edge information. This paper describes a method to find correspondences between images with very poor edge information -for instance a painting with a cloudless sky- and its application to...
This paper presents a new local binocular stereo matching algorithm. A self-adapting matching score is used to measure the dissimilarity of two corresponding pixels. In matching cost aggregation step, we replace the cost of each pixel with the average cost of selected neighboring pixels based on edge pixels information to limit cost aggregation within the same segment, which can preserve the shape...
There are many approaches to pedestrian detection in collision avoidance systems depending on the sensors (visible light, thermal infrared, radar, laser scanner) used for acquiring the data and the features (depth, shape, motion) used for detection. In this paper we present a method for shape based pedestrian detection in traffic scenes using a stereo vision system for acquiring the image frames and...
Matching is a central problem in pattern recognition and computer vision, its applications includes object detection and tracking. HCMA (hierarchical chamfer matching) is a classical image matching algorithm, which utilizes the edge information to match the images robustly and the multi-resolution pyramid to accelerate the matching process. However, for images with cluttered background and high resolution,...
This paper put forwards a corner detection solution and develops and builds a vision system depending upon the TMS320DM642 as the core, which can realize the image collection and display, implement the corner detection algorithm. Through the extended UART interfaces, this system can communicate with mobile robots of power lines. Corner coordinates obtained from the algorithm of this system can be...
3D model is used for vision based vehicle location. An improved Hausdorff distance based on edge-strength is proposed to evaluate the similarity between 3D model projection and image feature, and to establish location optimization function In order to avoid local minimum during optimization, estimation of distribution algorithm concerning related multi-variables is used. The relationship between matching...
Camera calibration is one of critical steps in computer vision, also an exhaustive process because substantial human computer interactions are frequently required to deal with the matching problem. In this paper, an automatic matching method of markers for camera calibration is presented based on the local architecture characteristics of a new planar circle pattern, which can be applied to a wide...
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