采用激光视觉测量技术对钢轨全断面廓形进行检测,在动态测量过程中由于车辆的随机振动,会影响钢轨轮廓数据的检测精度。因此,在高速动态条件下实现检测钢轨轮廓与标准廓形高精度自动匹配,是当前轨道廓形检测中面临的关键问题。在分析国...采用激光视觉测量技术对钢轨全断面廓形进行检测,在动态测量过程中由于车辆的随机振动,会影响钢轨轮廓数据的检测精度。因此,在高速动态条件下实现检测钢轨轮廓与标准廓形高精度自动匹配,是当前轨道廓形检测中面临的关键问题。在分析国内外钢轨廓形检测、廓形匹配现状的基础上,通过对目前采用最多的迭代最近点ICP(Iterative Close Point)算法进行简化,同时优化匹配过程中的对应点搜索策略,在保证匹配精度的前提下,解决了钢轨廓形检测中的匹配问题,达到实时性检测的需求。将该算法运用在地铁轨道检测设备中,验证了该方法的有效性。展开更多
In this paper, we proposed a novel Two-layer Motion Estimation(TME) which searches motion vectors on two layers with partial distortion measures in order to reduce the overwhelming computational complexity of Motion E...In this paper, we proposed a novel Two-layer Motion Estimation(TME) which searches motion vectors on two layers with partial distortion measures in order to reduce the overwhelming computational complexity of Motion Estimation(ME) in video coding. A layer is an image which is derived from the reference frame such that the sum of a block of pixels in the reference frame determines the point of a layer. It has been noticed on different video sequences that many motion vectors on the layers are the same as those searched on the reference frame. The proposed TME performs a coarse search on the first layer to identify the small region in which the best candidate block is likely to be positioned and then perform local refined search on the next layer to pick the best candidate block in the located small area. The key feature of TME is its flexibility of mixing with any fast search algorithm. Experimental results on a wide variety of video sequences show that the proposed algorithm has achieved both fast speed and good motion prediction quality when compared to well known as well as the state-of-the-art fast block matching algorithms.展开更多
Pattern matching is a very important topic in computer science. It has been used in various applications such as information retrieval, virus scanning, DNA sequence analysis, data mining, machine learning, network sec...Pattern matching is a very important topic in computer science. It has been used in various applications such as information retrieval, virus scanning, DNA sequence analysis, data mining, machine learning, network security and pattern recognition. This paper has presented a new pattern matching algorithm—Enhanced ERS-A, which is an improvement over ERS-S algorithm. In ERS-A, two sliding windows are used to scan the text from the left and the right simultaneously. The proposed algorithm also scans the text from the left and the right simultaneously as well as making comparisons with the pattern from both sides simultaneously. The comparisons done between the text and the pattern are done from both sides in parallel. The shift technique used in the Enhanced ERS-A is the four consecutive characters in the text immediately following the pattern window. The experimental results show that the Enhanced ERS-A has enhanced the process of pattern matching by reducing the number of comparisons performed.展开更多
This paper presents an efficient pattern matching algorithm (FSW). FSW improves the searching process for a pattern in a text. It scans the text with the help of four sliding windows. The windows are equal to the leng...This paper presents an efficient pattern matching algorithm (FSW). FSW improves the searching process for a pattern in a text. It scans the text with the help of four sliding windows. The windows are equal to the length of the pattern, allowing multiple alignments in the searching process. The text is divided into two parts;each part is scanned from both sides simultaneously using two sliding windows. The four windows slide in parallel in both parts of the text. The comparisons done between the text and the pattern are done from both of the pattern sides in parallel. The conducted experiments show that FSW achieves the best overall results in the number of attempts and the number of character comparisons compared to the pattern matching algorithms: Two Sliding Windows (TSW), Enhanced Two Sliding Windows algorithm (ETSW) and Berry-Ravindran algorithm (BR). The best time case is calculated and found to be??while the average case time complexity is??.展开更多
文摘采用激光视觉测量技术对钢轨全断面廓形进行检测,在动态测量过程中由于车辆的随机振动,会影响钢轨轮廓数据的检测精度。因此,在高速动态条件下实现检测钢轨轮廓与标准廓形高精度自动匹配,是当前轨道廓形检测中面临的关键问题。在分析国内外钢轨廓形检测、廓形匹配现状的基础上,通过对目前采用最多的迭代最近点ICP(Iterative Close Point)算法进行简化,同时优化匹配过程中的对应点搜索策略,在保证匹配精度的前提下,解决了钢轨廓形检测中的匹配问题,达到实时性检测的需求。将该算法运用在地铁轨道检测设备中,验证了该方法的有效性。
文摘In this paper, we proposed a novel Two-layer Motion Estimation(TME) which searches motion vectors on two layers with partial distortion measures in order to reduce the overwhelming computational complexity of Motion Estimation(ME) in video coding. A layer is an image which is derived from the reference frame such that the sum of a block of pixels in the reference frame determines the point of a layer. It has been noticed on different video sequences that many motion vectors on the layers are the same as those searched on the reference frame. The proposed TME performs a coarse search on the first layer to identify the small region in which the best candidate block is likely to be positioned and then perform local refined search on the next layer to pick the best candidate block in the located small area. The key feature of TME is its flexibility of mixing with any fast search algorithm. Experimental results on a wide variety of video sequences show that the proposed algorithm has achieved both fast speed and good motion prediction quality when compared to well known as well as the state-of-the-art fast block matching algorithms.
文摘Pattern matching is a very important topic in computer science. It has been used in various applications such as information retrieval, virus scanning, DNA sequence analysis, data mining, machine learning, network security and pattern recognition. This paper has presented a new pattern matching algorithm—Enhanced ERS-A, which is an improvement over ERS-S algorithm. In ERS-A, two sliding windows are used to scan the text from the left and the right simultaneously. The proposed algorithm also scans the text from the left and the right simultaneously as well as making comparisons with the pattern from both sides simultaneously. The comparisons done between the text and the pattern are done from both sides in parallel. The shift technique used in the Enhanced ERS-A is the four consecutive characters in the text immediately following the pattern window. The experimental results show that the Enhanced ERS-A has enhanced the process of pattern matching by reducing the number of comparisons performed.
文摘This paper presents an efficient pattern matching algorithm (FSW). FSW improves the searching process for a pattern in a text. It scans the text with the help of four sliding windows. The windows are equal to the length of the pattern, allowing multiple alignments in the searching process. The text is divided into two parts;each part is scanned from both sides simultaneously using two sliding windows. The four windows slide in parallel in both parts of the text. The comparisons done between the text and the pattern are done from both of the pattern sides in parallel. The conducted experiments show that FSW achieves the best overall results in the number of attempts and the number of character comparisons compared to the pattern matching algorithms: Two Sliding Windows (TSW), Enhanced Two Sliding Windows algorithm (ETSW) and Berry-Ravindran algorithm (BR). The best time case is calculated and found to be??while the average case time complexity is??.
