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Characterisation of tool marks on cartridge cases by combining multiple images

IET image processing 2012年第7期6卷 854-862页

作者： Leloglu, U. M. TUBITAK UZAY TR-06531 Ankara Turkey

The characteristic marks left by firearms on cartridge cases (CCs) during firing are used by forensic experts to identify CCs fired from the same firearm;however, the nature of the tool marks on the CCs is not well understood. The objective of this study is to separate the tool marks i.e., the signal, from the background signal and the noise and thereby understand its peculiarities. To extract the signal, which is much weaker than the noise, second-order derivatives of three-dimensional images of the surfaces of a series of CCs fired from the same firearm were used. Instead of using rigid body transformation, the images are first registered based on estimated planar homographies;then unwanted areas, including the headstamp are masked out. Aligned images are merged by weighted averaging using estimated signal and noise variances, which are also used for calculating signal and noise spectra. Wiener filtering is applied to further increase the signal-to-noise ratio. The effectiveness of the method is demonstrated on real data. It is also shown that breech face marks exist on the outer ring, a feature typically ignored in automatic matching. In addition, visual results obtained by reconstructing the surface from second-order derivatives are presented.

关键词： forensic experts Filtering methods in signal processing Military circuits, components, and equipment firearm second order derivatives computer vision and image processing techniques image processing planar homographies estimation Optical, image and video signal processing Wiener filters weapons noise variances three-dimensional images background signal signal-to-noise ratio CC automatic matching law Military engineering computing tool mark characterisation noise spectra signal extraction Wiener filtering military computing cartridge cases

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Vanishing point detection in corridors: using Hough transform and K-means clustering

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IET computer vision 2012年第1期6卷 40-51页

作者： Ebrahimpour, R. Rasoolinezhad, R. Hajiabolhasani, Z. Ebrahimi, M. Shahid Rajaee Teacher Training Univ Dept Elect & Comp Engn Brain & Intelligent Syst Res Lab Tehran Iran SCS Inst Res Fundamental Sci IPM Tehran Iran Islamic Azad Univ S Tehran Branch Tehran Iran

One of the main challenges in steering a vehicle or a robot is the detection of appropriate heading. Many solutions have been proposed during the past few decades to overcome the difficulties of intelligent navigation platforms. In this study, the authors try to introduce a new procedure for finding the vanishing point based on the visual information and K-Means clustering. Unlike other solutions the authors do not need to find the intersection of lines to extract the vanishing point. This has reduced the complexity and the processing time of our algorithm to a large extent. The authors have imported the minimum possible information to the Hough space by using only two pixels (the points) of each line (start point and end point) instead of hundreds of pixels that form a line. This has reduced the mathematical complexity of our algorithm while maintaining very efficient functioning. The most important and unique characteristic of our algorithm is the usage of processed data for other important tasks in navigation such as mapping and localisation.

关键词： Hough transforms vehicle steering Hough space mobile robots intelligent navigation pattern clustering robot vision visual information Integral transforms in numerical analysis vanishing point detection corridors Mobile robots computer vision and image processing techniques path planning image recognition K-means clustering Hough transform

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Visual sensitivity-based low-bit-rate image compression algorithm

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IET image processing 2012年第7期6卷 910-918页

作者： Xia, Q. Li, X. Zhuo, L. Lam, K. M. Beijing Univ Technol Signal & Informat Proc Lab Beijing Peoples R China Hong Kong Polytech Univ Dept Elect & Informat Engn Ctr Signal Proc Kowloon Hong Kong Peoples R China

In this study, the authors present a visual sensitivity-based low-bit-rate image compression algorithm. The authors algorithm combines both visual sensitivity and compression techniques so that a higher compression rate, with satisfactory visual quality, can be achieved. In the coding process, the input image is divided into blocks, and each block is classified as an edge block (EB), a textural block (TB) or a flat block (FB). For EBs, which are most important to the subjective quality of decoded images, the standard Joint Photographic Experts Group (JPEG) coding scheme with a tolerant quantisation step is employed so as to restrict the blocking artefacts caused by the quantisation error to an acceptable level. For FBs, a skipping scheme is employed on blocks in the compression process so as to save the bits. The coding of the skip blocks, identified by the skipping scheme, will make reference to the reconstructed regions of the image in the encoding process. Owing to the masking effects of the human visual system on high-frequency textures, standard JPEG compression coding with a greater quantisation step is employed on the down-scaled version of non-skip blocks and TBs. Experimental results show the superior performance of our method in terms of both compression efficiency and visual quality.

关键词： blocking artefacts edge block classification textural block classification visual sensitivity-based low-bit-rate image compression algorithm data compression image reconstruction Joint Photographic Experts Group computer vision and image processing techniques image and video coding image coding standard JPEG compression coding skipping scheme quantisation (signal) visual quality image classification high-frequency textures image reconstruction regions image texture block codes skip block coding flat block classification quantisation error JPEG coding scheme

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Colourisation in Yxy colour space for purple fringing correction

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IET image processing 2012年第7期6卷 891-900页

作者： Lee, D. -K. Kim, B. -K. Park, R. -H. Sogang Univ Dept Elect Engn Sch Engn Seoul 121742 South Korea

Purple fringing is an undesirable colour artefact in images acquired from digital cameras. As digital cameras are getting smaller these days with supporting high-quality images, purple fringing has become a serious problem. This study proposes an effective purple fringing correction method using colourisation in the Yxy colour space. In the proposed method, a chromaticity diagram-based method is used to detect the purple fringed region (PFR), and then this region is corrected by colourisation. The colours of intact pixels near the PFR are set to those of the seed pixels. Experimental results using a number of test images with purple fringing show that the regions, which are corrected by the proposed method, look more natural to human observers than those that are corrected by other existing methods.

关键词： digital cameras PFR detection human observers seed pixels purple fringed region detection image sensors computer vision and image processing techniques object detection chromaticity diagram-based method purple fringing correction method Optical, image and video signal processing colour artefact image colour analysis cameras intact pixels Yxy colour space

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Accuracy and numerical stability of high-order polar harmonic transforms

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IET image processing 2012年第6期6卷 617-626页

作者： Singh, C. Upneja, R. Punjabi Univ Dept Comp Sci Patiala Punjab India

Invariant moments and transforms are a special kind of statistical measure designed to remain constant after some transformations, such as object rotation, scaling, translation or image illumination changes, in order to improve the reliability of a pattern recognition system. Polar harmonic transforms (PHTs) are one of such image descriptors based on a set of orthogonal projection bases, which are better rated in comparison with other moments and transforms because they possess less redundant information. PHTs suffer from geometric error and numerical integration error. Geometric error is caused when a square image is mapped into a unit circular disk, which cannot exactly match the square domain. Numerical integration error is caused when the integration is approximated by zeroth-order summation. We propose a computational framework based on numerical integration approach that reduces the geometric error and the numerical integration error simultaneously. The effect of the improved accuracy in the PHTs is analysed for rotation invariance, scale invariance and image noise. Various numerical experiments demonstrate that the effect of these errors is much more prominent in small images and, therefore the proposed method is suitable for applications involving small images, such as in optical character recognition and template-matching applications.

关键词： integration numerical integration error statistical analysis optical character recognition scale invariance PHT statistical measure unit circular disk computer vision and image processing techniques image processing template-matching invariant moment geometric error object rotation zeroth-order summation Optical, image and video signal processing Integral transforms numerical stability Numerical integration and differentiation image noise pattern recognition Integral transforms in numerical analysis object scaling image illumination transforms orthogonal projection bases rotation invariance high-order polar harmonic transform image descriptor

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image zooming using directional cubic convolution interpolation

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IET image processing 2012年第6期6卷 627-634页

作者： Zhou, D. Shen, X. Dong, W. N China Elect Power Univ Sch Control & Comp Engn Beijing Peoples R China CAS Inst Automat LIAMA NLPR Beijing Peoples R China

image-zooming is a technique of producing a high-resolution image from its low-resolution counterpart. It is also called image interpolation because it is usually implemented by interpolation. Keys' cubic convolution ( CC) interpolation method has become a standard in the image interpolation field, but CC interpolates indiscriminately the missing pixels in the horizontal or vertical direction and typically incurs blurring, blocking, ringing or other artefacts. In this study, the authors propose a novel edge-directed CC interpolation scheme which can adapt to the varying edge structures of images. The authors also give an estimation method of the strong edge for a missing pixel location, which guides the interpolation for the missing pixel. The authors' method can preserve the sharp edges and details of images with notable suppression of the artefacts that usually occur with CC interpolation. The experiment results demonstrate that the authors' method outperforms significantly CC interpolation in terms of both subjective and objective measures.

关键词： image resolution high resolution image artefact suppression edge directed CC interpolation image zooming computer vision and image processing techniques image blurring missing pixel location image blocking Interpolation and function approximation (numerical analysis) objective measures subjective measures Optical, image and video signal processing directional cubic convolution interpolation interpolation

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Robust watermarking using fractional wavelet packet transform

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IET image processing 2012年第4期6卷 386-397页

作者： Bhatnagar, G. Raman, B. Wu, Q. M. J. Univ Windsor Dept Elect & Comp Engn Windsor ON N9B 3P4 Canada Indian Inst Technol Dept Math Roorkee Uttar Pradesh India

In this study, the concept of fractional wavelet packet transform is explored with its application in digital watermarking. The core idea of the proposed watermarking scheme is to decompose an image via fractional wavelet packet transform and then a reference image is created by changing the positions of all frequency sub-bands at each level with respect to some rule which is secret and only known to the owner/creator. For embedding, the reference image is segmented into non-overlapping blocks and modify its singular values with the watermark singular values. Finally, a reliable watermark extraction algorithm is developed for the extraction of watermark from the distorted image. The feasibility of this method and its robustness against different kind of attacks are verified by computer simulations.

关键词： computer vision and image processing techniques image watermarking image and video coding fractional wavelet packet transform digital watermarking Data security wavelet transforms watermark extraction algorithm Integral transforms image segmentation

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Local binary pattern and its derivatives for face recognition

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IET computer vision 2012年第5期6卷 480-488页

作者： Suruliandi, A. Meena, K. Rose, R. Reena Manonmaniam Sundaranar Univ Dept Comp Sci & Engn Tirunelveli Tamil Nadu India Sardar Raja Coll Engn Dept Comp Sci & Engn Tirunelveli 627808 Tamil Nadu India St Xaviers Catholic Engn Coll Dept Comp Sci & Engn Kanyakumari Tamil Nadu India

Texture is the surface property that is used to identify and recognise objects. This property is widely used in many applications including texture-based face recognition systems, surveillance, identity verification and so on. The Local binary pattern (LBP) texture method is most successful for face recognition. Owing to the great success of LBP, recently many models, which are variants of LBP have been proposed for texture analysis. Some of the derivatives of LBPs are multivariate local binary pattern, centre symmetric local binary pattern, local binary pattern variance, dominant local binary pattern, advanced local binary pattern, local texture pattern (LTP) and local derivative pattern (LDP). In this scenario, it is essential to review, whether LBP or their derivatives perform better for face recognition. The real-time challenges such as illumination changes, rotations, angle variations and facial expression variations are evaluated by different LBP-based models. Experiments were conducted on the Japanese female facial expression, YALE and FRGC version2 databases. The results show that LDP and LTP perform much better than the other LBP-based models.

关键词： multivariate local binary pattern YALE databases advanced local binary pattern face recognition systems LBP-based models angle variations image recognition LDP Spatial and pictorial databases visual databases facial expression variations centre symmetric local binary pattern local derivative pattern surveillance face recognition local binary pattern texture method surface property illumination changes computer vision and image processing techniques Japanese female facial expression FRGC version2 databases image texture local binary pattern variance identity verification dominant local binary pattern

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Visual secret sharing for general access structures by random grids

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IET INFORMATION SECURITY 2012年第4期6卷 299-309页

作者： Wu, X. Sun, W. Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China Sun Yat Sen Univ Sch Software Guangzhou 510006 Guangdong Peoples R China

Visual secret sharing (VSS) is a way to protect a secret image among a group of participants by using the notions of perfect ciphers and secret sharing. However, each share generated by conventional VSS is m times as big as the original secret image, where m is called pixel expansion. Random grid (RG) is an alternative approach to implement VSS without pixel expansion. However, reported RG-based VSS methods are threshold schemes. In this study, RG-based VSS for general access structures is presented. Secret image is encoded into n RGs while qualified sets can recover the secret visually and forbidden sets cannot. The proposed scheme is a generalisation of the threshold methods, where those reported RG-based schemes can be considered as the special cases of the proposed scheme. Experimental results are provided, demonstrating the effectiveness and advantages of the proposed scheme.

关键词： general access structure visual secret sharing cryptography computer vision and image processing techniques image and video coding image coding secret image Data security Cryptography pixel expansion RG-based VSS method threshold method random grid approach perfect cipher

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Subface hidden Markov models coupled with a universal occlusion model for partially occluded face recognition

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IET BIOMETRICS 2012年第3期1卷 149-159页

作者： Huang, S. -M. Yang, J. -F. Natl Cheng Kung Univ Adv Optoelect Technol Ctr Inst Comp & Commun Engn Dept Elect Engn Tainan 70101 Taiwan

In this study, a novel face recognition framework based on the grammatical face models has been proposed to tackle partial occlusion problem. The grammatical face model represents a face by five isolated 'subface', forehead, eyes, nose, mouth and chin models in cooperation with 'occlusion' models. With the creations of 'subface' and 'occlusion' models, the authors then define a facial grammar to manipulate 'subface' and 'occlusion' models for constructing various composite face models structurally. Furthermore, the authors also introduce a universal 'occlusion' model, which could handle general occlusions to improve the robustness and flexibility of grammatical face models. The proposed face recognition system could overcome two problems. One is to resolve the problem of face recognition with partial occlusions;the other is to overcome a challenge of training face models from occluded face images only. Experimental results carried out on AR facial database reveal that the proposed approach outperforms the state-of-the-art methods.

关键词： hidden Markov models face recognition framework partially occluded face recognition isolated subface model image recognition facial grammar AR facial database face representation mouth model occluded face image eyes model composite face model face recognition universal occlusion model computer vision and image processing techniques chin model Markov processes subface hidden Markov model nose model grammatical face model partial occlusion problem image representation forehead model

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