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In this paper, we present an accurate and robust license plate localization approach based on the Support Vector Machine (SVM) classifier. We impose the license plate localization as a classifier based binary recognition problem. The images of our database exhibit various illumination conditions (daytime, dark night). For the problem of illumination effects, we use the algorithm of Scale Invariant...
Local feature based approaches have gotten great success in object detection and recognition in recent years. In this paper, a novel local based feature, Structured Local Edge Pattern Moment (SLEPm), is proposed for pedestrian detection in the sliding window framework. SLEPm encodes not only the statistical information but also the structure and spatial information of object for pedestrian detection...
This paper introduces a method of hand-raising gestures detection in indoor environments, using shape and edge features. Past approaches have detected the gestures through recognizing the action for isolated or seated persons. Here, to deal with movements, non-rigidity and partially occlusions of human bodies, the gestures are detected by searching for raised hands and arms rather than recognizing...
Efficiently and accurately detecting pedestrian plays a very important role in many computer vision applications such as Intelligent Transportation System and Safety Driving Assistant. This paper puts forwards a two-stage pedestrian detection method based on machine vision. Firstly, the expanded Haar-like characteristic is selected and calculated using integral map and the pedestrian detection cascaded...
Recognizing smiles is of much importance for detecting happy moods. Gabor features are conventionally widely applied to facial expression recognition, but the number of Gabor features is usually too large. We proposed to use pyramid histogram of oriented gradients (PHOG) as the features extracted for smile recognition in this paper. The comparisons between the PHOG and Gabor features using a publicly...
In this paper SVM algorithm is applied to classify the scenery video types in compressed domain. Firstly we extract video sequences randomly from scenery video and detect representative frames from the video sequences; secondly we extract features such as color layout, dominant color, edge histogram and face feature; then according to SVM, representative frames are classified as natural scenery, personality,...
An efficient face recognition system by the combination of support vector machines (SVMs) and elastic graph matching was presented. The implementations of this system are as follows: Firstly, the two eyes of a face image are detected by using SVMs approach, and the detected eye coordinates are used as reference points for alignment and normalization of the face image. Secondly, elastic graph matching...
Cataract is the leading cause of blindness worldwide. Two automatic grading systems are presented in this paper for nuclear cataract and cortical cataract diagnosis respectively. Model-based approach was applied to detect anatomical structure in slit-lamp images. Features were extracted based on the lens structure and severity of nuclear cataract was predicted using support vector machines (SVM) regression...
In this paper, a new feature for text verification is proposed. The difficulties for the selection of features for text verification (FTV) are first discussed, followed by two principles for the FTV: the FTV should minimize the influence of backgrounds, and it should also be expressive enough for all the texts varied in structures prominently. In this paper, we exploit different block partition methods...
The increasing number of demanding consumer video applications, as exemplified by cell phone and other low-cost digital cameras, has boosted interest in no-reference objective image and video quality assessment (QA). In this paper, we focus on no-reference image and video blur assessment. There already exist a number of no-reference blur metrics, but most are based on evaluating the widths of intensity...
State-of-the-art approaches for detecting filament-like structures in noisy images rely on filters optimized for signals of a particular shape, such as an ideal edge or ridge. While these approaches are optimal when the image conforms to these ideal shapes, their performance quickly degrades on many types of real data where the image deviates from the ideal model, and when noise processes violate...
In this paper, a support vector regression (SVR) based method is proposed to detect a geometric feature such as line equation, corner point and angle degree between straight lines in an image. Digital image with geometric figures is collected and transmitted into computer. Median filter is used to reduce noise in the original gray scale image. Then image contour with single-pixel width is obtained...
As an important image feature, a corner takes significant position in camera calibration, pattern recognition and image matching area. A large amount of image corner points are the intersecting points of the edges of polygons. A corner point extracting method based on support vector for regression (SVR) was proposed aimed at extracting intersecting points. First, a digital image of geometric figures...
The ability to sort agricultural produce automatically is very important. This paper addresses one way to identify agricultural produce based on their shape. The techniques used are based on support vector machines. The images of the produce are loaded into MATLAB and the features extracted using image processing techniques based on edge detection. These features are then input to a classifier; i...
In this paper, we present a two-stage vision-based approach to detect front and rear vehicle views in road scene images using eigenspace and a support vector machine for classification. The first stage is hypothesis generation (HG), in which potential vehicles are hypothesized. During the hypothesis generation step, we use a vertical, horizontal edge map to create potential regions where vehicles...
Traffic density and flow are important inputs for an intelligent transport system (ITS) to better manage traffic congestion. Presently, this is obtained through loop detectors (LD), traffic radars and surveillance cameras. However, installing loop detectors and traffic radars tends to be difficult and costly. Currently, a more popular way of circumventing this is to develop a sort of virtual loop...
As a basic two-class classifier, support vector machine (SVM) has been proved to perform well in image classification, which is one of the most common tasks of image processing. However, for the n-class problem in image classification, SVM treats it as n two-class problems, in this way, unclassifiable regions exist. In this paper, we introduce fuzzy support vector machine (FSVM) and define a membership...
Video shot boundary detection is one of the fundamental tasks of video indexing and retrieval applications. Although many methods have been proposed for this task, finding a general and robust shot boundary method that is able to handle the various transition types caused by photo flashes, rapid camera movement and object movement is still challenging. We present a novel approach for detecting video...
With the increasing amount of multimedia data, content-based image retrieval attracts many researchers of various fields in an effort to automate data analysis and indexing. In this paper, we propose a content-based semantic indexing method which annotates images automatically using concepts and textual description. In order to bridge the "semantic gap" between the low-level descriptors...
We propose a novel target recognition algorithm for classification of three types of ground vehicles in the moving and stationary target acquisition and recognition public release database. Algorithms that produce classifiers with large margins, such as support vector machines (SVMs), AdaBoost, etc. are receiving more and more attention in the literature. A real application of AdaBoost for synthetic...
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