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Implementation of the Hough Transform for Iris Detection and Segmentation  [PDF]
Francisco Javier Paulín-Martínez, Alberto Lara-Guevara, Rosa María Romero-González, Hugo Jiménez-Hernández
Advances in Molecular Imaging (AMI) , 2019, DOI: 10.4236/ami.2019.91002
Abstract: The iris is used as a reference for the study of unique biometric marks in people. The analysis of how to extract the iris characteristic information represents a fundamental challenge in image analysis, due to the implications it presents: detection of relevant information, data coding schemes, etc. For this reason, in the search for extraction of useful and characteristic information, approximations have been proposed for its analysis. In this article, it is presented a scheme to extract the relevant information based on the Hough transform. This transform helps to find primitive geometries in the irises, which are used to characterize each one of these. The results of the implementation of the algorithm of the Hough transform applied to the location and segmentation of the iris by means of its circumference are presented in the paper. Two public databases of iris images were used: UBIRIS V2 and CASIA-IrisV4, which were acquired under the same conditions and controlled environments. In the pre-processing stage the edges are found from the noise elimination in the image through the Canny detector. Subsequently, to the images of the detected edges, the Hough transform is applied to the disposition of the geometries detected.
Extended Standard Hough Transform for Analytical Line Recognition
Abdoulaye SERE,Oumarou SIE,Eric ANDRES
International Journal of Advanced Computer Sciences and Applications , 2013,
Abstract: 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 preimage. Many alternatives of approximation could be established for the sinusoid curves of the dual of a pixel to get new algorithms of line recognition.
Lookup Table Hough Transform for Real Time Range Image Segmentation and Featureless Co-Registration  [PDF]
Ben Gorte, George Sithole
Journal of Sensor Technology (JST) , 2012, DOI: 10.4236/jst.2012.23021
Abstract: The paper addresses range image segmentation, particularly of data recorded by range cameras, such as the Microsoft Kinect and the Mesa Swissranger SR4000. These devices record range images at video frame rates and allow for acquisition of 3-dimensional measurement sequences that can be used for 3D reconstruction of indoor environments from moving platforms. The role of segmentation is twofold. First the necessary image co-registration can be based on corresponding segments, instead of corresponding point features (which is common practice currently). Secondly, the segments can be used during subsequent object modelling. By realisising that planar regions in disparity images can be modelled as linear functions of the image coordinates, having integer values for both domain and range, the paper introduces a lookup table based implementation of local Hough transform, allowing to obtain good segmentation results at high speeds.
Hough Transform to Study the Magnetic Confinement of Solar Spicules  [PDF]
E. Tavabi, S. Koutchmy, A. Ajabshirizadeh
Journal of Modern Physics (JMP) , 2012, DOI: 10.4236/jmp.2012.311223
Abstract: One of the important parameters of the ubiquitous spicules rising intermittently above the surface of the Sun is the variation of spicule spline orientation with respect to the solar coordinates, presumably reflecting the focusing of ejection by the coronal magnetic field. Here we first use a method of tracing limb spicules using a combination of second derivative operators in multiple directions around each pixel to enhance the visibility of fine linear part of spicules. Furthermore, the Hough transform is used for a statistical analysis of spicule orientations in different regions around the solar limb, from the pole to the equator. Our results show a large difference of spicule apparent tilt angles in regions of: 1) the solar poles, 2) the equator, 3) the active regions and 4) the coronal holes. Spicules are visible in a radial direction in polar regions with a tilt angle <20°. The tilt angle is even reduced inside a coronal hole (open magnetic field lines) to 10 degrees and at the lower latitude the tilt angle reaches values in excess of 50 degree. Usually, around an active region they show a wide range of apparent angle variations from –60 to +60 degrees, which is in close resemblance to the rosettes made of dark mottles and fibrils seen in projection with the solar disk.
A Method of Road Extraction from Remote Sensing Images Based on Shape Features and Width-Tolerant Hough Transform

张国英, 赵鹏, 宋科科
Journal of Image and Signal Processing (JISP) , 2014, DOI: 10.12677/JISP.2014.32006
Road extraction from high-resolution remote sensing image is an important and difficult task. The road-extraction method, which uses the integration shape features and the improved Hough transform, is proposed in this paper. Firstly, the image is segmented, and then the linear and curve roads are obtained by using several object shape features. Secondly, the step of road extraction is using the improved Hough transform method to deal with the road targets. Finally, the extracted roads are regulated by combining the edge information. In experiments, the images including the better gray uniform of road and the worse illuminated of road surface were chosen, and the results prove that the method of this study is promising.
重庆大学学报 , 2006, DOI: 10.11835/j.issn.1000-582X.2006.02.009
Abstract: 提出了一种根据差值图像的线段参数进行印章识别的方法.首先完成目标图像与模板图像的精配准,然后对图像进行差值计算,用霍夫变换得到差值图像的直线段数.并用此直线段数作出判决.实验结果表明,利用该算法进行识别时正确性高,且所用时间短,效果好.所提供的方法在对6类目标60幅图像进行识别时总识别正确率高于85%.
Research of Fog Driving Scenarios and Visibility Recognition Algorithm Based on Video

朱舞雪, 宋春林
Journal of Image and Signal Processing (JISP) , 2015, DOI: 10.12677/JISP.2015.43008
Obtaining real-time, comprehensive and accurate road traffic information is the important pre-condition and basic guarantee to prevent traffic accidents, and also is the key to realize the urban traffic intelligent. For recognition of fog driving scenarios and visibility, the traditional algorithm has the problems of high complexity, poor robustness, and more using in fixed scene; it is difficult to apply to mobile driving scenarios. This paper proposed a fog and visibility estimation algorithm based on monocular vision. The algorithm, based on the law of Koschmieder, compresses Hough transformation vote space and reduces calculation amount and complexity by limiting polar angle and radius. Custom regional growth solves the problem of poor accuracy in the mobile scenarios’ road segmentation. The weighted average of luminance method which is used in estimation of inflection point can effectively remove interference and ensure accuracy. The simulation results show that the algorithm can realize the recognition of fog and visibility in mobile scenarios with high accuracy, real-time performance and robustness.
An Object Recognition and Identification System Using the Hough Transform Method
Jaruwan Toontham,Chaiyapon Thongchaisuratkrul
International Journal of Information and Electronics Engineering , 2013, DOI: 10.7763/ijiee.2013.v3.272
Abstract: This paper presents an object recognition and identification system using the Hough Transform method. The process starts from imported images into the system by webcam, detected image edge by fuzzy, recognized the object by Hough Transform, and separated the objects by the robot arm. Three objects type; triangle, rectangular and, rigid circle are used. The results showed that the objects can be isolated 96%, 96%, and 98% correct for triangular, rectangular, and rigid circle respectively.
Combined Object Detection and Segmentation
Jarich Vansteenberge,Masayuki Mukunoki,Michihiko Minoh
International Journal of Machine Learning and Computing , 2013, DOI: 10.7763/ijmlc.2013.v3.273
Abstract: We develop a method for combined object detection and segmentation in natural scene. In our approach segmentation and detection are considered as two faces of the same coin that should be combined into a single framework. There are two main steps in our strategy. First we focus on the learning of a visual vocabulary that efficiently encompasses objects’ appearance, spatial configuration and underlying segmentation. This vocabulary is used within a Hough voting framework to produces object’s configuration. The second step consists in searching for valid objects’ configurations by interpreting and scoring them in terms of both detection and segmentation. This allows us to prune false detections and hallucinated object-like segmentation. Experiments show the advantage of the combined approach and the improvements over recent related methods.
The Detection of Quartz that Based on the Improved Hough Transform
Yin Yaping,Wang Yanlin,Liu Guili,Li Dong
Information Technology Journal , 2012,
Abstract: In the process of product defects detection, Hough algorithm is widely used in the image angles examines. Not only while operating it needs very big memory space, the speed and the efficiency is slowly. On this foundation an improved Hough algorithm is quoted in the image examines of Crystal chip. It can reduce calculation capacity and shorten the operation time, so, it meets the time of Crystal chips in the industry test.
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