Fast template matching using bounded partial correlation

This paper describes a novel, fast template-matching technique, referred to as bounded partial correlation (BPC), based on the normalised cross-correlation (NCC) function. The technique consists in checking at each search position a suitable elimination condition relying on the evaluation of an upper-bound for the NCC function. The check allows for rapidly skipping the positions that cannot provide a better degree of match with respect to the current best-matching one. The upper-bounding function incorporates partial information from the actual cross-correlation function and can be calculated very efficiently using a recursive scheme. We show also a simple improvement to the basic BPC formulation that provides additional computational benefits and renders the technique more robust with respect to the parameters choice. Received: 2 November 2000 / Accepted: 25 July 2001 Correspondence to: L. Di Stefano     

Scale-invariant template matching using histogram of dominant gradients

This paper presents a histogram-based template matching method that copes with the large scale difference between target and template images. Most of the previous template matching methods are sensitive to the scale difference between target and template images because the features extracted from the images are changed according to the scale of the images. To overcome this limitation, we introduce the concept of dominant gradients and describe an image as the feature that is tolerant to scale changes. To this end, we first extract the dominant gradients of a template image and represent the template image as the grids of histograms of the dominant gradients. Then, the arbitrary regions of a target image with various locations and scales are matched with the template image via histogram matching. Experimental results show that the proposed method is more robust to scale difference than previous template matching techniques.     

Optimal template matching by nonorthogonal image expansion using restoration

In this paper we present a novel approach for template matching. The basic principle is expansion matching and it entails signal expansion into a set of nonorthogonal templatesimilar basis functions. The coefficients of this expansion signify the presence of the template in the corresponding locations in the image. We demonstrate that this matching technique is robust in conditions of noise, superposition, and severe occlusion. A new and more practical discriminative signal-to-noise ratio (DSNR) for matching is proposed that considers even the filter's off-center response to the template as “noise”. We show that expansion yields the optimal linear operator that maximizes the DSNR and results in a sharp response to the matched template. Theoretical and experimental comparisons of expansion matching and the widely used correlation matching demonstrate the superiority of our approach. Correlation matching (also known as matched filtering) yields broad peaks and spurious responses, both of which hamper good detection. We also show that the special case of expansion with a dense set of self-similar basis functions is equivalent to signal restoration. Expansion matching can be implemented by restoration techniques and also by our recently developed lattice architecture.     

Surface hydrothermal alteration mapping at Vulcano Island using MIVIS data

Remotely sensed data (airborne hyperspectral Multispectral Infrared and Visible Imaging Spectroradiometer (MIVIS) data) were used to map active hydrothermal areas at Vulcano island (Sicily), related to a shallow magmatic chamber inducing hot fluid movements in the overlying rocks. A multispectral analysis was carried out using selected MIVIS band combinations and field spectra of selected altered surfaces. Results were checked by field survey, especially in the most active La Fossa crater area, where the zonation of a superficial high sulphidation hydrothermal system was reconstructed. The band selection used was able to clearly discriminate between fresh and hydrothermally altered rocks, especially at La Fossa crater; but differences between advanced argillic and the silicic alteration facies, as identified by field spectra, were not recognized, probably due to the occurrence of fumaroles. Despite the bias introduced by vegetation cover, illumination conditions and buildings, previously unrecognized sites of potential hydrothermal alteration and fumaroles were mapped in the northern sector of Vulcano island.     

Artificial landmark-based underwater localization for AUVs using weighted template matching

This paper deals with vision-based localization techniques in structured underwater environments. For underwater robots, accurate localization is necessary to perform complex missions successfully, but few sensors are available for accurate localization in the underwater environment. Among the available sensors, cameras are very useful for performing short-range tasks despite harsh underwater conditions including low visibility, noise, and large areas of featureless scene. To mitigate these problems, we design artificial landmarks to be utilized with a camera for localization, and propose a novel vision-based object detection technique and apply it to the Monte Carlo localization (MCL) algorithm, a map-based localization technique. In the image processing step, a novel correlation coefficient using a weighted sum, multiple-template-based object selection, and color-based image segmentation methods are proposed to improve the conventional approach. In the localization step, to apply the landmark detection results to MCL, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform and the results are discussed.     

Privacy aware image template matching in clouds using ambient data

Cloud computing is ideal for image storage and processing because it provides enormously scalable storage and processing resources at low cost. One of the major drawbacks of cloud computing, however, is the lack of robust mechanisms for the users to control the privacy of the data they farm out to the clouds. In this paper, we develop an image encoding scheme that enhances the privacy of image data that is outsourced to the clouds for processing. Unlike previously proposed image encryption schemes, our encoding scheme allows different forms of pixel-level image processing to take place in the clouds while the actual image is not revealed to the cloud provider. Our encoding scheme uses a chaotic map to transform the image after it is masked with an arbitrarily chosen ambient image. We use template matching as a common image processing task to demonstrate the ability of our scheme to perform computations on privacy enhanced images. A simplified prototype of the image processing system was implemented and the experimental results are presented in this paper.     

New scale invariant template matching technique using hyper space image representation

A new approach for the template image matching is being presented. The method first converts the image into edges, then, the vital information of these edges has been presented as a set of vectors in a four dimensional hyper-space. A modified Radon Transform has been proposed to facilitate this vectorization process. All the above processing is being done offline for the main image of the area. The template image has also been vectorized in a same fashion in real time which is to be matched with the main image. A vector matching algorithm has been proposed to deliver match location with a very low computational cost. It works for a wide range of template scaling and noise conditions which were not there in the previous algorithms found in the literature.     

多方向模板的构造及匹配的快速算法

多方向模板匹配是图像处理的重要方法。对原有的Prewitt模板进行了扩充，构造了新的多方向模板，建立了相应的快速模板匹配算法。在图像处理中，通过多方向模板，图像得到了加强，并且提取了图像相关的线性特征，实行快速算法在理论上比经典算法快4．57倍，节省了运行时间。     

两种改进的模板匹配识别算法

在开发在线轮胎编码图像自动识别系统时,通过对现有常用的几种识别算法分析与研究,提出了两种改进的标准模板匹配识别算法,分别是基于特征加权的模板匹配算法和基于特征块的模板匹配算法,两种改进的算法都以抽取字符特征为基础,结合模糊原理进行识别,经过理论分析与实际测试,两种改进的识别算法都进一步提高了图像字符的识别率。     

Comparison of multi-temporal ASTER images for hydrothermal alteration mapping using a fractal-aided SAM method

The shortwave infrared (SWIR) spectral bands of four multi-temporal images acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA’s Terra platform were analysed for evaluating the effects of acquisition properties and atmospheric pre-processing levels on the resulting hydrothermal alteration maps a using the fractal-aided Spectral Angle Mapper (SAM) method. Three ASTER level-1B products covering the Sar Cheshmeh area in Iran were used for hydrothermal alteration mapping. These images were converted to surface reflectance using the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) method. The low reflectance of band 5 of the level-1B products was compensated for by using the spectra of collected rock samples. Level-2 (AST2B05S) SWIR ASTER images that had already been processed were also used. Reference spectra of the main hydrothermal alteration types were extracted for each product. The threshold angles were determined using the real value–area (RV–A) fractal technique. Then, SAM classification was carried out to map hydrothermal alteration for every product. It is concluded that the level-1B products that had been converted to reflectances have a better spectral contrast than the AST2B05S product. Summer images with lower tilt angle and higher solar elevation should be used to increase the accuracy of the image classification and minimize the effect of vegetation on the spectra of index minerals. By comparing the resulting hydrothermal alteration maps with known alteration types using a confusion matrix, it was shown that the application of the RV–A fractal technique to produce less biased threshold angles increases the accuracy of SAM classification.     

Identification of copy-move and splicing based forgeries using advanced SURF and revised template matching

Multimedia Tools and Applications - Various image tampering detection approaches are used to find the variations or inconsistencies in statistical image features. But still these techniques lack...     

模板匹配技术在图像识别中的应用

在图像目标识别技术的研究应用中,模板匹配技术是其中一个重要的研究方向,它具有算法简单、计算量小以及识别率高的特点。介绍了几种改进的模板匹配技术在图像处理、模式识别等领域的应用,包括有条码识别、生物特征识别技术(人脸识别、指纹识别等)、车牌识别、字符识别、飞机识别等。     

A program for template matching of protein sequences

The matching of a template to a protein sequence is simplified by treating it as a special case of sequence alignment. Restriction of the distances between motifs in the template controls against spurious matches within very long sequences. The program using this algorithm is fast enough to be used in scanning large databases for sequences matching a complex template.     

Template matching using the parametric template vector with translation,rotation and scale invariance

A new method for the template matching, invariant to image translation, rotation and scaling, is proposed. In the first step of our approach, the ring-projection transform (RPT) process is used to convert the 2D template in a circular region into a 1D gray-level signal as a function of radius. The advantages of the RPT process are that it owns the characteristic of rotation invariance and reduces the computational complexity of normalized correlation (NC). Then, the template matching is performed by constructing a parametric template vector (PTV) of the 1D gray-level signal with differently scaled templates of the object. The merits of our approach are that it not only obtains rotation invariance, but also scale invariance Additionally, our approach is conceptually simple, easy to implement and only one training image is needed for the training phase. Experimental results show that the computational time of the proposed approach is faster and the performance is better than the parametric template (PT) method and the affine moment invariants (AMIs) method in the image rotation or scaling. Moreover, our approach not only enjoys high accurate rate under the changes of translation, rotation and scale, but also estimates the scaling value of the target object in the input scene. Experiments with Gaussian noise demonstrate that the proposed algorithm is robust to detect the target object with the changes of translation, orientation and scale. This indicates that our approach is suitable for on-line template matching with scene translation, rotation and scaling.     

Detection of marine aerosol particles in coastal zones using satellite imagery

Regions of brightness variations are common in visible and near-infrared satellites images from clear coastal regions. The variations have been hypothesized to be caused by aerosol particles in the marine boundary layer. The hypothesis was tested using in situ particle measurements collected near the time of satellite overpasses. Boundary-layer particle concentrations related to the brightness variations: high concentrations existed in bright regions and vice versa. This result indicates that, in regions over the ocean free of clouds, sunglint and whitecaps, the visible and near-infrared sensors aboard certain orbiting meteorological satellites can detect variations in the concentrations of haze particles in the marine boundary layer.     

基于模板匹配的电子元器件针脚检测方法

相关系数法模板匹配是数字摄影检测中的一种经典的基于灰度的匹配方法.提出了一种基于模板匹配的电子器件针脚检测方法,以实际针脚影像和自动生成的标准模板的相关系数作为匹配测度以确定针脚的实际位置.同时为了达到生产流水线快速检测的要求,首先在粗一级的金字塔影像上获取初始位置再反算到原始影像进行精密定位,实验结果表明该方法的定位精度高,速度快,可以满足工业检测的要求.     

A novel rotation/scale invariant template matching algorithm using weighted adaptive lifting scheme transform

This paper presents a novel algorithm for detecting user-selected objects in given test images based on a new adaptive lifting scheme transform. Given an object as a template, we first select a set of coefficients as object features in the wavelet transform domain and then build an adaptive transform based on the selected features. The goal of the new adaptive transform is to vanish the selected features in the transform domain. After applying both non-adaptive and adaptive transforms to a given test image, the corresponding transform domain coefficients are compared for detecting the object of interest. In addition, the proposed detection algorithm is combined with the proper log-polar mapping model in the parametric template space to attain rotation/scale invariance property. Finally, we have verified the properties of our proposed algorithm with experimental results.     

基于模板匹配的网络评论倾向性分析

不同语境的词语其倾向性有差异。针对此问题,研究了二义词倾向性识别,词语倾向性识别及评论倾向性分析。建立了结构模板集和核心词模板集,用模板匹配方法判断词语在特定句子中的倾向性。根据词语的倾向性并考虑副词和反问句对倾向性的影响,计算评论的倾向性。实验结果表明,可提高网络评论倾向性分析的准确率。     

图像数字水印中的模板匹配检测方法

基于对数极坐标映射(LPM),设计了图像数字水印技术中的模板匹配检测方法.该模板匹配检测方法的特点是:在图像数字水印的嵌入过程中,从对数极坐标域中切取一块模板匹配信息;计算该模板匹配信息与加入水印后的图像在LPM域中的相位谱的相关系数来进行水印的检测工作.这种方法不使用原始图像的全部信息,减少了相关性检验的计算时间,提高了工作效率.实验结果表明该方法对图像中数字水印具有较强的检测能力.