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In this paper, we present a non-symmetry and anti-packing object pattern representation model (NAM) for object detection. A set of distinctive sub-patterns (object parts) is constructed from a set of sample images of the object class; object pattern are then represented using sub-patterns, together with spatial relations observed among the sub-patterns. Many feature descriptors can be used to describe...
In order to improve the citrus grading accuracy, fractal dimensions which characterize the color and shape features of citrus fruit were analyzed. Samples were from Citrus unshiu Marc.cv.unbergii Nakai. For each sample, images from peduncle, calyx and two opposite sides were collected. These four images were cut, removed backgrounds, and converted from RGB space to HSI one, then by the following methods,...
The goal of this work is the fully-automated detection of cellulose fibre cross sections in microtomy images. A lack of significant appearance information makes edges the only reliable cue for detection. We present a novel and highly discriminative edge fragment descriptor that represents angular relations between fragment points. We train a Random Forest with a plurality of these descriptors including...
Fire can lead to major financial losses to industries. Consequently, it is very crucial to develop a reliable method to detect an occurrence of fire. In this research, the algorithms for flame detection using video processing will be proposed. System identification will be used to obtain a process model of the flame. This paper stresses on the flame detection algorithm. The results show that detection...
Ear Rows is an important agricultural character in Maize (Zea mays L.). In order to exam feasibility of ear rows counting method by machine vision, a new method was raised. This method is based on edge marker and discrete curvature. 78 digital images of 4 maize cultivars were scanned from 2 sides if maize fragment face. Based on this, we find that that the number is mostly 12-18, and the detecting...
Image encoding using interest points is a common technique in computer vision. In this paper we present a scale and rotation invariant shape centered interest point (SCIP) detector. By means of detecting singularities in Gradient Vector Flow (GVF) fields we find points of high symmetry in the image. Due to the nature of the underlying GVF field we can employ our features to group together edge-based...
An efficient method for rapidly detecting circles using edge-tracking and evidence-collecting is presented. First, edge points are tracked to form series of edge chains. Then three points are randomly selected from each edge chain to obtain a possible circle. In the end, an evidence-collecting process is applied to determine whether the possible circle is a true one or not. During the evidence-collecting...
High precision identification of feature points is an important technology and one of the bases of computer vision, image analysis and image processing. In the practical applications, the feature points can not be identified easily in various conditions of light illumination, visual angle, texture, and perspective projection. And in many cases, the size of feature point is small, the context is uncertain...
Describing local patches to register image keypoints is an important task for building a huge database from video frames. When searching for an efficient descriptor, task is twofold: features must describe the featuring patches at a high efficiency, while the dimensionality should be kept at a manageable low value. The main assumption in finding local descriptors is the defect of continuity in the...
Human detection remains a challenge in computer vision due to highly articulated body postures, viewpoints changes, varying illumination conditions and cluttered background. Because of these difficulties, most of the previous publications often focus only on low-articulated postures, e.g. pedestrians, in still images. In this paper, we propose a new method to detect a human region from still images...
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...
The extraction of lane mark is an essential step for several vision-based systems in intelligent transportation applications. In this paper, we propose a novel method for lane detection using a new active contour model. The new model is a modified version of the classical C-V model in gradient domain. The initial level set curve can be anywhere in the image without changing the segmentation result...
Object recognition and reconstruction are pivot technologies both in computer vision and in machine intelligence. There are a number of techniques for object recognition, such as pattern comparison, feature matching, and boundary detection and so on, which heavily depend on the rigid depiction of projected images of the object. This consequently results in that even recognized it is still remain tough...
Recently, there has been an increasing demand for computer-vision-based measurement and inspection at the production line. So far lots of inspection processes are carried out by human workers, hence it is almost impossible to check the fault of all parts, coming from part-feeding system, with only human inspection because of time limitation as well as working hardship. Therefore, most of manual inspection...
In order to use a robot in the construction automation filed, we proposed the concept of Bolting Robot and a visual servo control scheme to track a bolting tool to a bolt hole in the structural steel frame. For estimating a location of a bolt hole, Circular Hough Transform (CHT) was used to extract circles. Generally, CHT is computationally complex due to a power of the dimensionality of a circle...
In this paper, we propose a new vision based method to recognize the entering and exiting events from video sequences via motion analysis. Without sensors, the proposed approach is invariant to body shape and clothing as a combination of edge detection, motion history image and geometrical characteristic of the human shape in MHI sequences. The proposed method includes several applications such as...
Shape representation is a very important issue in computer vision and pattern recognition. This paper presents a novel shape representation algorithm based on equilateral polygonal approximation. Firstly, the problem and definition of equilateral polygonal approximation are presented in this paper. Then a new equilateral polygonal approximation method based on detecting optimal edge length using genetic...
Human detection is the task of finding presence and position of human beings in images, In this paper, we apply scale space theory to detection human in still images. By integrating scale space theory with histogram of oriented gradients(HOG), we designed a new feature descriptor called scale space histogam of oriented gradients (SS-HOG). SS-HOG focus on the multiple scale property of describe an...
Nowadays an increasing research interest in the field of biotechnology has been drawn to achieve reliable information from model organisms. C. Elegans nematode worm is one of the major animals. Machine vision analysis of this animal needs to solve many important problems, e.g. detection of each individual in population images, movement patterns of isolated and overlapped worms and so on. In this paper,...
We propose a novel set of medial feature interest points based on gradient vector flow (GVF) fields [18]. We exploit the long ranging GVF fields for symmetry estimation by calculating the flux flow on it. We propose interest points that are located on maxima of that flux flow and offer a straight forward way to estimate salient local scales. The features owe their robustness in clutter to the nature...
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