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.     

Localization of impulsive disturbances in audio signals using template matching

In this paper, a new solution to the problem of elimination of impulsive disturbances from audio signals, based on the matched filtering technique, is proposed. The new approach stems from the observation that a large proportion of noise pulses corrupting audio recordings have highly repetitive shapes that match several typical “patterns”. In many cases a representative set of exemplary pulse waveforms can be extracted from the episodes of silence preceding and succeeding the recorded audio material. Based on such a set, a relatively small number of typical noise patterns, called click templates, can be established. To localize noise pulses, the appropriately modified click templates can be correlated with the sequence of one-step-ahead prediction errors yielded by the model-based signal predictor. It is shown that template matching is an efficient and computationally affordable disturbance localization technique – when combined with the classical detection method based on autoregressive modeling, it can improve restoration results. Since click templates can be created for a particular set of recordings, obtained using a particular audio equipment, an important feature of the proposed approach is its source adaptivity. Even though the paper is focused on restoration of archive recordings, the proposed approach is useful in a much wider context, e.g., it can be applied to elimination of impulsive disturbances corrupting telecommunication channels.     

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.     

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.     

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.     

改进的模板匹配算法

在图像消旋消抖处理中通常运用到模板匹配算法,但在战场目标抗抖动的运用中,由于装甲战车车载图像跟踪系统受到地形地物的影响,会产生剧烈扰动,会产生匹配错误。建立了图像运动模型,根据图像灰度特征,对模板匹配算法进行改进。根据几何距离约束特征点的性质,运用特征点校正去除伪特征点,较好地消除误匹配,达到战场图像消旋消抖的要求。     

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.     

Robust template matching with angle location using dynamic feature pairs updating

This work proposes a novel method for template matching in the wild. Different from the previous methods to search the matching position, our method obtains further ability on the angle location by dynamically updating corresponding feature pairs and rigid transformation parameters, which result in mutual enhancement of both feature extraction and template location. We propose a robust objective function with a valid feature selection for template matching against to noise disturbance, background changing, object deformation and partial occlusion. A hierarchical search strategy is used by adjusting the size of feature patch to improve the matching effectiveness. In addition, we extend the proposed method to match image sequences. It is beneficial to propagate reasonable feature pairs to a sequential object as initialization, recalling a stable tracking result. Extensive experiments are tested on the public database with challenging images and sequences. Experimental results demonstrate the merits of the proposed method compared to some state-of-the-art matching methods.     

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。     

一种改进的模版匹配识别算法

通过对现有常用的几种模板匹配算法的分析与研究,提出了一种全区域特征加权模板匹配识别算法,它是对特征加权的模板匹配算法的一种改进。经过理论分析与实际测试,这种改进的识别算法进一步降低了字符的误识率。     

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...     

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.     

适于人脸检测的模板匹配快速算法

为提高人脸检测中模板匹配的速度,在积分图像基础上,提出和应用平方积分图像,实现了一种计算速度与图像窗口大小无关的快速灰度均值和方差算法。应用这种快速算法,结合对灰度分布标准化近似计算公式、相关系数和平均偏差计算公式的变换,以及灰度分布标准化处理时省略拷贝图像窗口及窗口灰度值变换等不必要的步骤,大大提高了模板匹配速度。人脸检测实验证明了这种算法的有效性。     

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。     

Colon segmentation and colonic polyp detection using cellular neural networks and three-dimensional template matching

Abstract: In this study, an automatic three-dimensional computer-aided detection system for colonic polyps was developed. Computer-aided detection for computed tomography colonography aims at facilitating the detection of colonic polyps. First, the colon regions of whole computed tomography images were carefully segmented to reduce computational burden and prevent false positive detection. In this process, the colon regions were extracted by using a cellular neural network and then the regions of interest were determined. In order to improve the segmentation performance of the study, weights in the cellular neural network were calculated by three heuristic optimization techniques, namely genetic algorithm, differential evaluation and artificial immune system. Afterwards, a three-dimensional polyp template model was constructed to detect polyps on the segmented regions of interest. At the end of the template matching process, the volumes geometrically similar to the template were emhanced.