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In this paper, we have implemented and tested a system of detection and recognition of road signs. The approach taken in this work consists of two main modules: a sensor module, which is based on color segmentation and shape detection where we converted the images to the HSV color space, then labeled the detected regions and tested for their shape. A recognition module, Template Matching, whose role...
In order to identify a large number of very similar objects, a novel recognition approach is proposed by mean of combination of two dynamic grouping algorithms, the visual processing mechanism, PCA and multi-pathway SVM. The samples have been segmented to appropriate groups by grouping features, and then features with rotation invariance and translation invariance of each group are extracted. Finally,...
In this paper we are going to apply four descriptors (GIST, PHOG, SURF and Centrist) and two classifiers (Artificial Neural Network (ANN) and Support Vector Machines (SVM)) for handwritten mathematical symbols recognition to achieve a comparative study based on the recognition rate.
The high complexity of multi-scale, category-level object detection in cluttered scenes is efficiently handled by Hough voting methods. However, the main shortcoming of the approach is that mutually dependent local observations are independently casting their votes for intrinsically global object properties such as object scale. Object hypotheses are then assumed to be a mere sum of their part votes...
This paper presents a Ring Projection Transforms (RPT) for recognizing an object in automation system. Based on the Coarse-fine strategy and Compute Unified Device Architecture (CUDA), we developed a recognition model on GPGPU (General-Purpose computing on Graphics Processing Units) scheme. As experimental validation indicates, our scheme achieved a better performance in terms of processing time compared...
License plate recognition (LPR) plays a significant role throughout this busy world, owing to the rise in vehicles day by day. Stealing of vehicles, breaking traffic rules, coming into restricted space also are increasing linearly, thus to dam this act registration code recognition is intended. Among the fundamental process steps such as detection of number plate, segmentation of characters and recognition...
License plate recognition (LPR) plays a major role in this busy world, as the number of vehicles increases day by day, theft of vehicles, breaking traffic rules, entering restricted area are also increases linearly, so to block this act license plate recognition system is designed. License Plate Recognition systems basically consist of 3 main processing steps such as: Detection of number plate, Segmentation...
In this paper, a detailed conception of an embedded system of road sign recognition algorithms based on color segmentation, shape analysis and template matching has been made. These techniques are poorly adapted to the Arab context, since some signs are written with Arabic letters. The illumination changes are the greatest obstacle in our work. Therefore, in the first module of the system there is...
This paper presents a new method which extends the Standard Hough Transform for the recognition of naive or standard line in a noisy picture. The proposed idea conserves the power of the Standard Hough Transform particularly a limited size of the parameter space and the recognition of vertical lines. The dual of a segment, and the dual of a pixel have been proposed to lead to a new definition of the...
License plate detection and recognition is one of the most important aspects of applying computer techniques towards intelligent transportation systems. Detecting the accurate location of a license plate from a vehicle image is the most crucial step of a license plate detection system. This paper describes a proposing of a new region-based license plate detection method based on a symbol analysis...
The paper deals with an application of spectral analyses to recognition and classification of sound signals. Spectral analysis is a possible method to obtain information for classification of signals. The short time spectral analyses of segmented sound signals of a car engine are presented. The application of classification with neural network is shown. The real signal of sound car engines was used.
The main objective of this paper is to verify bank cheques by using account number and account holder's signature present on the cheque image. Main problem is to exact localization of active regions among non-active contours in the image. Here, we locate the regions based on the prior knowledge of Cartesian coordinate space. It further involves various steps such as Gray-Scale conversion, Segmenting...
2D barcode recognition technique and system play an important role in the industry application. It is extremely challenging to locate and recognize barcodes when the background is cluttered and the illumination is uneven. In this paper, we propose a hierarchical framework for 2D Data Matrix recognition and further introduce the 2D barcode recognition system based on the proposed method. The superiority...
We propose an effective method to achieve position invariance in the application of optical character recognition (OCR). We normalise the position of all inputs based on their symmetry features. The generalized symmetry transform (GST) is used to determine the symmetry features prior to classification by a probabilistic neural network (PNN). We used the United States Postal Service (USPS) data set...
This paper presents a new bag-of-words based algorithm for object recognition. Our algorithm also includes five steps: feature detection and representation, codebook generation, learning and recognition. All features are extracted as dense grids of images instead of interest point for computationally efficiency and effectiveness. While features are described by histograms of oriented gradients (HOG)...
This paper presents an interactive emotion recognition system using support vector machine for human-robot interaction. The proposed emotion recognition algorithm is composed of Harr wavelet transform, principal component analysis (PCA) method, and support vector machine (SVM). This algorithm is shown effective and useful in achieving both face identification and facial expression recognition. The...
The aim of this paper is to apply distance transform on curved space (DTOCS) to grayscale images of human tissue samples. Also a new approximated path DTOCS (APDTOCS), which approximates distances on curved space using only the end points of the paths, is proposed. APDTOCS reveals more detail than standard DTOCS especially in parts of the image where the texture is complex and has a lot of small details...
In this paper, we extract model-based gait features and investigate the time-frequency representations of the feature signals. A novel gait recognition approach is proposed, which is based on time-frequency analysis of gait feature signals using the Wigner distribution. Time-frequency analysis using the Wigner distribution is aimed at capturing gait information that is not extractable using other...
This paper introduces a new computer recognition algorithm for image texture recognition. Using this algorithm, the texture characteristic of image is extracted exactly for analysis. 2-d bidirectional median filtering is proposed to make image de-noising an ideal state. An image correction algorithm with Hough transfer on local computation is presented to obtain an image with better position state...
The present work is a contribution in the field of printed Tifinaghe characters recognition. The input pattern is subject to some special treatments. The recognition system consists of three phases: pre-processing, features extraction and recognition. In the pre-processing phase, we applied four operations: digitization, noise reduction, skew correction and segmentation. Then the features extraction...
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