MAC: magnetostatic active contour model

We propose an active contour model using an external force field that is based on magnetostatics and hypothesized magnetic interactions between the active contour and object boundaries. The major contribution of the method is that the interaction of its forces can greatly improve the active contour in capturing complex geometries and dealing with difficult initializations, weak edges and broken boundaries. The proposed method is shown to achieve significant improvements when compared against six well-known and state-of-the-art shape recovery methods, including the geodesic snake, the generalized version of GVF snake, the combined geodesic and GVF snake, and the charged particle model.     

Multiple response surface optimization with correlated data

Setting of process variables to meet the required specification of quality characteristics is an important problem in the process quality control. There are often several conflicts in quality characteristics, which should be simultaneously satisfied. These types of problems are called “Multiple Response Optimization” (MRO). When quality characteristics are correlated, MRO problems may become increasingly difficult. In design of experiments, identifying covariates effects could reduce error and uncovered variances as well as give more insight about the process. This study aims to identify process variables to consider correlated covariates and correlated quality characteristics. It also accommodates dispersion effects and specification limits as well as location effects in a unified framework based on desirability functions. The features of the proposed method are investigated and the results are compared with some existing techniques by applying two numerical examples.     

Colour tonality inspection using eigenspace features

In industrial quality inspection of colour texture surfaces, such as ceramic tiles or fabrics, it is important to maintain a consistent colour shade or tonality during production. We present a multidimensional histogram method using a novelty detection scheme to inspect the surfaces. The image noise, introduced by the imaging system, is found mainly to affect the chromatic channels. For colour tonality inspection, the difference between images is very subtle and comparison in the noise dominated chromatic channels is error prone. We perform vector-ordered colour smoothing and extract a localised feature vector at each pixel. The resulting histogram represents an encapsulation of local and global information. Principal component analysis (PCA) is performed on this multidimensional feature space of an automatically selected reference image to obtain reliable colour shade features, which results in a reference eigenspace. Then unseen product images are projected onto this eigenspace and compared for tonality defect detection using histogram comparison. The proposed method is compared and evaluated on a data set with groundtruth. Xianghua Xie is currently a Ph.D. student and a research assistant in the Department of Computer Science, University of Bristol, U.K. Prior to this, he received an M.Sc. degree in advanced computing with commendation from the University of Bristol in 2002 and a B.Sc. degree in environmental engineering from the Tongji University, Shanghai, P.R. China, in 2000. His current research interests are texture analysis, image segmentation, surface inspection, deformable models and historical document analysis. He is a student member of the BMVA, the IEE and the IEEE. Majid Mirmehdi received the B.Sc. (Hons.) and Ph.D. degrees in computer science in 1985 and 1991 respectively, from the City University, London. He has worked both in industry and in academia. He is currently a Reader in the Department of Computer Science at the University of Bristol, UK. His research interests include texture analysis, colour image analysis, medical imaging and document recognition. He has over 100 refereed conference and journal publications in these areas. He is an associate editor of the Pattern Analysis and Applications Journal. He is a member of the IEE, IEEE and a member and the Chairman of the British Machine Vision Association.     

Quality chain design and optimization by multiple response surface methodology

To maintain optimal quality characteristics in the defined specification limits is a vital decision for any industry and service system. To avoid nonconformity in outputs, the stream of variations and their potential causes must be identified so that the response variables fall into desirable limits across the manufacturing or service chain. Response surface methodology is considered as a powerful technique to facilitate the analysis of the mentioned problem. This paper presents the general quality chain design problem as a mathematical program and also proposes a method to solve it using multiple response surface methodology. An example of multistage processes is analyzed by the proposed approach to show its efficacies numerically and analytically.     

Temporal video segmentation and classification of edit effects

The process of shot break detection is a fundamental component in automatic video indexing, editing and archiving. This paper introduces a novel approach to the detection and classification of shot transitions in video sequences including cuts, fades and dissolves. It uses the average inter-frame correlation coefficient and block-based motion estimation to track image blocks through the video sequence and to distinguish changes caused by shot transitions from those caused by camera and object motion. We present a number of experiments in which we achieve better results compared with two established techniques.     

A non-contact method of capturing low-resolution text for OCR

Document recognition is a lively research area with much effort concentrated on optical character recognition. Less attention is paid to locating and extracting text from the general (non-desktop, non-scanner) environment. Such contact-free extraction of text from a general scene has applications in the context of wearable computing, robotic vision, point and click document capture, or as an aid for visually handicapped people. Here, a novel automatic text reading system is introduced using an active camera focused on text regions already located in the scene (using our recent work). Initially, a located region of text is analysed to determine the optimal zoom that would foveate onto it. Then a number of images are captured over the text region to construct a high-resolution mosaic composite of the whole region. This magnified image of the text is suitable for reading by humans or for recognition by OCR, or even for text-to speech synthesis. Although we employed a low resolution camera, we still obtained very good results. ID="A1"Correspondance and offprint requests to: Dr M. Mirmehdi, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK. Email: majid@cs.bris.ac.uk     

Optimization of Degree of Conformance in Multiresponse–Multistage Systems with a Simulation‐based Metaheuristic

In today's manufacturing and service systems, entities are progressed across the several stages of operations wherein one or more quality characteristic may be formed. The quality of final system outputs depends on the quality of intermediate characteristics as well as design parameters in each stage. This paper presents a new mathematical program to simultaneously optimize multiple quality characteristics in multiple stage systems. Multivariate form response surface methodology is applied with iterative seemingly unrelated regression as the estimation method to extract the relationships between the outputs and inputs in each stage. Because the intermediate response variables may act as covariates in the next stages, the probabilistic patterns of the response surfaces are considered by association with the quality of the previous stages. The objective function in the proposed model is the acceptance probability of the outputs based on predefined specification limits. A combination of Monte Carlo simulation and the genetic algorithm is also proposed to solve the final stochastic optimization model. At the end, the applicability of the proposed approach is illustrated by a numerical example. Copyright © 2014 John Wiley & Sons, Ltd.     

Computer vision elastography: speckle adaptive motion estimation for elastography using ultrasound sequences

We present the development and validation of an image based speckle tracking methodology, for determining temporal two-dimensional (2-D) axial and lateral displacement and strain fields from ultrasound video streams. We refine a multiple scale region matching approach incorporating novel solutions to known speckle tracking problems. Key contributions include automatic similarity measure selection to adapt to varying speckle density, quantifying trajectory fields, and spatiotemporal elastograms. Results are validated using tissue mimicking phantoms and in vitro data, before applying them to in vivo musculoskeletal ultrasound sequences. The method presented has the potential to improve clinical knowledge of tendon pathology from carpel tunnel syndrome, inflammation from implants, sport injuries, and many others.     

Correction to "MAC: Magnetostatic Active Contour Model" [Apr 08 632-646]

In the above titled paper (ibid., vol. 30, no. 4, pp. 632-646, Apr 08), there was an error in a definition. The correct definition is presented here.