The computation of a shape's orientation is a common task in the area of computervision and image processing, being used for example to define a local frame of reference and is helpful for recognition and registr...
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The computation of a shape's orientation is a common task in the area of computervision and image processing, being used for example to define a local frame of reference and is helpful for recognition and registration, robot manipulation, etc. It is usually an initial step or a part of data preprocessing in many image processing and computervision tasks. Thus, it is important to have a good solution for shape orientation because an unsuitable solution could lead to a big cumulative error at the end of the computing process. There are several approaches to the problem-most of them could be understood as the 'area based' ones, or at least they do not take into account all the boundary points (if a shape orientation measure is based on its encasing rectangle, only the convex hull points count, for example). Thus, the demand for a pure 'boundary based' method, where the orientation of the shape is dependent on the boundary points seems to be very reasonable. Such a method is presented in this paper. We are initially focused on the shapes having polygonal boundaries. We define the orientation of a polygonal shape by the line that maximises the total sum of squared lengths of all the boundary edge projections onto this line. The advantages and limitations of the new method are analysed. Next, we suggested how the method can be adapted in order to be applicable to a wider class than the initial method is. Finally, we introduced another modification of the method in such a way that the modified method can be applied to shapes with arbitrary boundaries. Several illustrative experiments are provided. (C) 2007 Elsevier Ltd. All rights reserved.
Latent fingerprint identification is of critical importance to law enforcement agencies in forensics application. While tremendous progress has been made in the field of automatic fingerprint matching, latent fingerpr...
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ISBN:
(纸本)9781424423392
Latent fingerprint identification is of critical importance to law enforcement agencies in forensics application. While tremendous progress has been made in the field of automatic fingerprint matching, latent fingerprint matching continues to be a difficult problem because the challenges involved in latent print matching are quite different from plain or rolled fingerprint matching. Poor quality of friction ridge impressions, small finger area and large non-linear distortion are some of the main difficulties in latent fingerprint matching. We propose a system for matching latent images to rolled fingerprints that takes into account the specific characteristics of the latent matching problem. In addition to minutiae additional features like orientation field and quality map are also used in our system. Experimental results on the NIST SD27 latent database indicate that the introduction of orientation field and quality, map to minutiae-based matching leads to good recognition performance despite the inherently difficult nature of the problem. We achieve the rank-20 accuracy of 93.4% in retrieving 258 latents from a background database of 2,258 rolled fingerprints.
One of the objectives of precision agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. This paper outlines an automatic computer...
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One of the objectives of precision agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. This paper outlines an automatic computervision-based approach for the detection and differential spraying of weeds in corn crops. The method is designed for post-emergence herbicide applications where weeds and corn plants display similar spectral signatures and the weeds appear irregularly distributed within the crop's field. The proposed strategy involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based measuring relationships between crop and weeds. The decision making determines the cells to be sprayed based on the computation of a posterior probability under a Bayesian framework. The a priori probability in this framework is computed taking into account the dynamic of the physical system (tractor) where the method is embedded. The main contributions of this paper are: (1) the combination of the image segmentation and decision making processes and (2) the decision making itself which exploits a previous knowledge which is mapped as the a priori probability. The performance of the method is illustrated by comparative analysis against some existing strategies. (c) 2007patternrecognition Society. Published by Elsevier Ltd. All rights reserved.
The inference of specular (mirror-like) shape is a particularly difficult problem because an image of a specular object is nothing but a distortion of the surrounding environment. Consequently, when the environment is...
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ISBN:
(纸本)9781424422425
The inference of specular (mirror-like) shape is a particularly difficult problem because an image of a specular object is nothing but a distortion of the surrounding environment. Consequently, when the environment is unknown, such an image would seem to convey little information about the shape itself It has recently been suggested (Adato et al., ICCV 2007) that observations of relative motion between a specular object and its environment can dramatically simplify the inference problem and allow one to recover shape without explicit knowledge of the environment content. However, this approach requires solving a non-linear PDE (the 'shape from specular flow equation') and analytic solutions are only known to exist for very constrained motions. In this paper, we consider the recovery of shape from specular flow under general motions. We show that while the 'shape from specular flow' PDE for a single motion is non-linear, we can combine observations of multiple specular flows from distinct relative motions to yield a linear set of equations. We derive necessary conditions for this procedure, discuss several numerical issues with their solution, and validate our results quantitatively using image data.
An approach for pearl shape classification using fuzzy patternrecognition based on Zernike moments was proposed. After a series of preprocessing on the pearl image obtained, transformed it to the polar coordinates, t...
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In this paper, we describe a novel type of feature for fast and accurate face detection. The feature is called Locally Assembled Binary (LAB) Haar feature. LAB feature is basically inspired by the success of Haar feat...
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ISBN:
(纸本)9781424422425
In this paper, we describe a novel type of feature for fast and accurate face detection. The feature is called Locally Assembled Binary (LAB) Haar feature. LAB feature is basically inspired by the success of Haar feature and Local Binary pattern (LBP)for face detection, but it is far beyond a simple combination. In our method, Haar features are modified to keep only the ordinal relationship (named by binary Haar feature) rather than the difference between the accumulated intensities. Several neighboring binary Haar features are then assembled to capture their co-occurrence with similar idea to LBP. We show that the feature is more efficient than Haar feature and LBP both in discriminating power and computational cost. Furthermore, a novel efficient detection method called feature-centric cascade is proposed to build an efficient detector, which is developed from the feature-centric method. Experimental results on the CMU+MIT frontal face test set and CMU profile test set show that the proposed method can achieve very good results and amazing detection speed.
In this paper, the automatic medical annotation task of the 2007 CLEF cross language image retrieval campaign (ImageCLEF) is described. The paper focusses on the images used, the task setup, and the results obtained i...
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In this paper, the automatic medical annotation task of the 2007 CLEF cross language image retrieval campaign (ImageCLEF) is described. The paper focusses on the images used, the task setup, and the results obtained in the evaluation campaign. Since 2005, the medical automatic image annotation task exists in ImageCLEF with increasing complexity to evaluate the performance of state-of-the-art methods for completely automatic annotation of medical images based on visual properties. The paper also describes the evolution of the task from its origin in 2005-2007. The 2007 task, comprising 11,000 fully annotated training images and 1000 test images to be annotated, is a realistic task with a large number of possible classes at different levels of detail. Detailed analysis of the methods across participating groups is presented with respect to the (i) image representation, (ii) classification method, and (iii) use of the class hierarchy. The results show that methods which build on local image descriptors and discriminative models are able to provide good predictions of the image classes, mostly by using techniques that were originally developed in the machine learning and computervision domain for object recognition in non-medical images. (C) 2008 Elsevier B.V. All rights reserved.
Segmentation is usually unable to cope with artifacts due to slight change in lighting conditions or object occlusion for instance. That is why perceptual grouping is often used to overcome segmentation's lacks. T...
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Segmentation is usually unable to cope with artifacts due to slight change in lighting conditions or object occlusion for instance. That is why perceptual grouping is often used to overcome segmentation's lacks. This refers to the ability of human visual system to impose structure and regularity over signal-based data. Gestalt psychologists have exhibited some properties which are used during perceptual grouping, such as proximity, continuity, or symmetry. Then, some implementations of these have been proposed in computervision. However, most of these works rely on contour-based primitives. Besides, they often use one single property to merge close regions, which may not be sufficiently robust. We propose a new framework for bottom-up perceptual grouping, which relies on a region-based segmentation. It allows us to use region or contour information, when it is the most suitable. Besides, we propose to trigger a grouping when several Gestalt properties support it. This could increase the robustness of perceptual grouping. We use Dempster-Shafer theory to combine the influence of several Gestalt properties over each grouping, as it is especially designed for this. We also present numerous promising results, which show the efficiency of our approach. (c) 2007 Elsevier Ltd. All rights reserved.
Touching characters are major problem of achieving higher recognition rate in Optical Character recognition (OCR). Present OCR systems do not perform well when adjacent characters touch. If characters are touched in g...
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ISBN:
(纸本)9781424442195
Touching characters are major problem of achieving higher recognition rate in Optical Character recognition (OCR). Present OCR systems do not perform well when adjacent characters touch. If characters are touched in graphical documents (e.g. map) then such touching string recognition is more difficult because in such documents touching characters appear in multi-oriented direction. In this paper, we present a scheme towards the recognition of English two-character multi-oriented touching strings. When two or more characters touch, the), generate a big cavity region at the background portion and we used this background information in our scheme. To handle the background information, convex hull is used. In this scheme, at first, a set of initial segmentation points is predicted based on the concave residues of the convex hull of the touching characters. Next, based on the initial points, we select some candidate segmentation lines. Finally the recognition confidence of two sub-images of a touching string, obtained from each candidate segmentation line is computed. The candidate segmentation line from which we get optimum confidence is the actual segmentation line and the corresponding characters in favour of which the two segmentation parts show optimum confidence is the recognition result of the touching string. To compute the recognition confidence, SVM classifier is used. The features used in the SVM are invariant to character orientation. Circular ring and convex hull ring based approach has been used along with angular information of the contour pixels of the character to make the feature rotation invariant. From the experiment we obtained encouraging result.
We propose an algorithm for the on-line automatic registration of multiple 3D surfaces acquired in a sequence by a new hand-held laser scanner. The laser emitter is coupled with an optical lens that spreads the light ...
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We propose an algorithm for the on-line automatic registration of multiple 3D surfaces acquired in a sequence by a new hand-held laser scanner. The laser emitter is coupled with an optical lens that spreads the light forming 19 parallel slits that are projected to the scene and acquired with subpixel accuracy by a camera. Splines are used to interpolate the acquired profiles to increase the sample of points and Delaunay triangulation is used to obtain the normal vectors at every point. A point-to-plane pair-wise registration method is proposed to align the surfaces in pairs while they are acquired, conforming paths and eventually cycles that are minimized once detected. The algorithm is specially designed for on-line applications and can be classified as a closing-the-loop technique, where there are not that many competing methods, though it has been compared to the literature. Experiments providing qualitative and quantitative evaluation are shown by means of synthetic and real data and we demonstrated the reliability of our technique. (C) 2007 Elsevier Ltd. All rights reserved.
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