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In this paper, a small set of features based on local appearance and texture is applied to the task of image recognition and classification. These features are used to train and subsequently test three different machine learning techniques, namely k-Nearest Neighbors (K-NN), Support Vector Machines (SVM) and Ensemble Learning (Bagging). A case study on a publicly available object classification dataset...
The design of traffic sign recognition (TSR) system, one important subsystem of Advanced Driver Assistance System (ADAS), has been a challenge practical problem for many years due to the complex issues like road environments, lighting conditions, occlusion, and so on. In this paper, we introduce a new TSR system, whose effectiveness has been tested through extensive experiments. The established TSR...
The problem of vehicle extraction using airborne laser scanning (ALS) is studied under the framework of object-based point cloud analysis (OBPA). Object extraction relies on the partitioning of raw ALS data into various segments approximating semantic entities followed by classification. A 3D segmentation method working directly on point cloud is used, which features the detection of local arbitrary...
In this paper, a work on representing plastic bottle shape using erosion based approach for an automated classification is reported. Morphological operations are used to describe the structure or form of an image. By using the two-dimensional description of plastic bottle silhouettes, edge detection of the object silhouette is performed followed by the erosion process. This work will compare two versions...
Contours of benign breast masses and malignant tumors in mammograms differ substantially in their shape and complexity; the former are usually round and smooth, whereas the latter are typically spiculated and irregular. We demonstrate the usefulness of fractal analysis via a frequency domain approach applied to one-dimensional signatures of the two-dimensional contours of breast masses. The 1/f model...
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...
Algorithm design of iris outer edge location is one of keys in iris recognition. It dose ask for an excellent performance as well as an acceptable running time. Low-level technologies and simple classifiers are employed in this paper to meet these needs. First of all, we propose a gradient computation for point detection to ensure a shorter running time. In this part, points can be located as many...
This paper presents a method for triangular and rectangular shapes detection in a road sign recognition system based on a three step algorithm: color segmentation, shape detection and neural network classification. The shape detector is based on the evaluation of the Sobel edges and Hough images in a region of interest detected by the color-based stage. During the tests performed the shape detector...
In this paper, we present a one dimensional descriptor for the two dimensional object silhouettes associated with each level of barycenter contour for multiple views shape matching and retrieval. Firstly, the barycenter contour is applied onto the shape contour. Then the averaging multi-triangle area representation (AMTAR) at each level of barycenter contour is computed as the shape descriptor. Finally,...
We used forward (FNN), Hermite(HNN), and Laguerre (LNN) neural networks to classify real and artificial fingerprints based on images obtained from optical coherence tomography (OCT). Use of a self-organizing map (SOM) after Gabor edge detection of OCT images of fingerprint and material surfaces resulted in the greatest classification performance when compared with moments based on color, texture,...
In this paper, we present a scheme towards recognition of English character in multi-scale and multi-oriented environments. Graphical document such as map consists of text lines which appear in different orientation. Sometimes, characters in a single word may follow a curvilinear way to annotate the graphical curve lines. For recognition of such multi-scale and multi-oriented characters a Support...
In this paper, an efficient approach for tablets vision inspection is proposed, which can detect missing and broken individual tablets in each blister after they are sealed. The images of tablets in blister can be obtained clearly using multi-lights. From these images the regions of tablets are segmented through thresholding method, and the tablets' shape contours are obtained by Canny edge detector...
Geometric active contours based on edges perform poorly in the presence of noise or clutter. When the edges have gaps or are indistinct, the contour leaks through the boundary. Furthermore, when spurious edge points that do not belong to the object are present in the image, the contour is stopped by them and either does not converge to the object boundary or there is oversegmentation. This paper addresses...
We address two-dimensional shape-based classification, considering shapes described by arbitrary sets of unlabeled points, or landmarks. This is relevant in practice because, in many applications, the points describing the shapes come from automatic processes, e.g., edge detection, thus without labels. Rather than attempting to compute point correspondences (a quagmire, when dealing with nontrivial...
Offline signature verification can be linked as a biometric classifier that categorizes a signature into two classes: genuine and forged. In this paper a contour matching algorithm is proposed that tracks the basic characteristic patterns in a sample signature and verifies it. It capitalizes on the geometrical properties of the signature and takes into account the inevitable intrapersonal variations...
This paper presents a novel circular augmented rotational trajectory (CART) algorithm to compute an R-space based shape descriptors which allow efficient shape matching, generalization and classification. The rotation invariant R-space representation can be used to detect invariant geometric features despite the presence of considerable noise and quantization errors. Moreover, the CART method is corner...
In many vision applications, there is a great demand for an edge detector which can produce edge maps with very different characteristics in nature, so that one of these edge maps may meet the requirements of the problem under consideration. Unfortunately it is not evident how to choose the desired or the optimum edge maps from these solutions that the edge detector offers. The proposed solutions...
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