18353926
Inverse validation for accurate range image registration with structured data
Automatic range image registration is a fundamental yet extremely difficult problem in machine vision. In this paper, we extend a promising registration algorithm, the geometric iterative closest point (GICP), for structured image data. The extended algorithm is based on a relaxation method combining the motion estimation results from the possible correspondences established by the GICP algorithm and those that are further evaluated by an inverse validation procedure. A comparative study based on real images has shown that the extended algorithm is more accurate and robust than the original algorithm.
15266073
Improving ICP with easy implementation for free-form surface matching
Automatic range image registration and matching is an attractive but unresolved problem in both the machine vision and pattern recognition literature. Since automatic range image registration and matching is inherently a very difficult problem, the algorithms developed are becoming more and more complicated. In this paper, we propose a novel practical algorithm for automatic free-form surface matching. This method directly manipulates the possible point matches established by the traditional ICP criterion based on both the collinearity and closeness constraints without any feature extraction, image pre-processing, or motion estimation from outliers corrupted data. A comparative study based on a large number of real range images has shown the accuracy and robustness of the novel algorithm.
26921590
Evaluating structural constraints for accurate range image registration
New technological developments in optics and electronics are rendering laser scanning systems cheaper and more accurate. Such systems can directly capture depth information from objects simplifying range image analysis and enlarging their applications scope. Accurate image registration algorithms represent a pivotal aspect of range image analysis which still require substantial improvements. While a large number of algorithms have been proposed, it is very important to compare the performance of different registration algorithms so that good algorithms can be selected for real applications. Unfortunately, most of these algorithms are iterative with a number of parameters initialised by users. The main disadvantages of these methods are that these parameters are often context dependent. Thus, while aiming to develop automatic registration algorithms instead of comparing the registration algorithms themselves, we compare the structural constraints based on a single registration algorithm(GICP). A large number of experiments using real range images demonstrate their effectiveness on improving the GICP algorithm.
10845590
Developing structural constraints for accurate registration of overlapping range images
Abstract Automatic image registration is an attractive and unresolved problem in the machine vision literature. This paper presents two novel structural constraints, namely proximity and closeness constraints, that improve both the accuracy and robustness of an existing motion consistency based algorithm (GICP) for automatic image registration. It also defines the conditions when such constraints are fired at specific points of the registration of two overlapping range images. The proximity constraint says that neighbouring points should be neighbouring before and after a rigid motion. The closeness constraint implements a local closest point search from the second image to the first image. While the GICP algorithm uses an exhaustive search for the closest points, in this paper, we employ the optimised k–d tree data structure to accelerate the closest point search. A large number of experiments based on real range images demonstrate that the combination of rigid motion constraints with these novel proximity and closeness constraints leads to a more accurate and robust evaluation of possible correspondences leading, in turn, to more accurate, robust and efficient automatic image registration results.
7923791
Discontinuity-Based Simplification of Free Form Surface From a Range Image
This paper improves an existing method for more accurate simplification of free form surface represented as dense points. The main improvement lies in two aspects: one is the introduction of a novel transformation of curvatures, the other is to propose sampling points using both curvature information and curvature variation information. The experimental results based on real images show that the original object surface has been better approximated and the majority of the surface discontinuities have been better preserved with considerably few sampled (5%) data points
35019950
A pseudo linearization method for accurate pose estimation from a single image
We propose a novel pseudo linearization method for accurate pose estimation from given correspondences between a 3D model and its projective image. A comparative study based on both synthetic data and real images has shown that the novel algorithm is accurate and robust.
6717587
Capacity of memoryless channels and block-fading channels with designable cardinality-constrained channel state feedback
A coding theorem is proved for memoryless channels when the channel state feedback of finite cardinality can be designed. Channel state information is estimated at the receiver and a function of the estimated channel state is causally fed back to the transmitter. The feedback link is assumed to be noiseless with a finite feedback alphabet, or equivalently, finite feedback rate. It is shown that the capacity can be achieved with a memoryless deterministic feedback and with a memoryless device which select transmitted symbols from a codeword of expanded alphabet according to current feedback. To characterize the capacity, we investigate the optimization of transmission and channel state feedback strategies. The optimization is performed for both channel capacity and error exponents. We show that the design of the optimal feedback scheme is identical to the design of scalar quantizer with modified distortion measures. We illustrate the optimization using Rayleigh block-fading channels. It is shown that the optimal transmission strategy has a general form of temporal water-filling in important cases. Furthermore, while feedback enhances the forward channel capacity more effectively in low-signal-to noise ratio (SNR) region compared with that of high-SNR region, the enhancement in error exponent is significant in both high- and low-SNR regions. This indicates that significant gain due to finite-rate channel state feedback is expected in practical systems in both SNR regions.
1966938
Robust midsagittal plane extraction from normal and pathological 3-D neuroradiology images
This paper focuses on extracting the ideal midsagittal plane (iMSP) from three-dimensional (3-D) normal and pathological neuroimages. The main challenges in this work are the structural asymmetry that may exist in pathological brains, and the anisotropic, unevenly sampled image data that is common in clinical practice. We present an edge-based, cross-correlation approach that decomposes the plane fitting problem into discovery of two-dimensional symmetry axes on each slice, followed by a robust estimation of plane parameters. The algorithm's tolerance to brain asymmetries, input image offsets and image noise is quantitatively evaluated. We find that the algorithm can extract the iMSP from input 3-D images with 1) large asymmetrical lesions; 2) arbitrary initial rotation offsets; 3) low signal-to-noise ratio or high bias field. The iMSP algorithm is compared with an approach based on maximization of mutual information registration, and is found to exhibit superior performance under adverse conditions. Finally, no statistically significant difference is found between the midsagittal plane computed by the iMSP algorithm and that estimated by two trained neuroradiologists.
1073181
Keeping Secrets within a Family: Rediscovering Parnas
David Parnas wrote several papers in the 1970’s and 1980’s that are now considered classics. The concepts he advocated such as information hiding and use of abstract interfaces are generally accepted as the appropriate way to design nontrivial software systems. However, not all of what he proposed has been fully appreciated and assimilated into our practices. Many of his simple, elegant ideas have been lost amongst the hype surrounding the technologies and methods that have arisen in the past two decades. This paper examines Parnas’s ideas, especially his emphasis on program families, and proposes that college-level computing science and software engineering curricula should renew their attention to these very important principles and techniques and present them in the context of contemporary software development.
258700
Cervical Cancer Detection Using SVM Based Feature Screening
We present a novel feature screening algorithm by deriving relevance measures from the decision boundary of Support Vector Ma- chines. It alleviates the "independence" assumption of traditional screen- ing methods, e.g. those based on Information Gain and Augmented Vari- ance Ratio, without sacrificing computational efficiency. We applied the proposed method to a bottom-up approach for automatic cervical cancer detection in multispectral microscopic thin PAP smear images. An initial set of around 4,000 multispectral texture features is effectively reduced to a computationally manageable size. The experimental results show significant improvements in pixel-level classification accuracy compared to traditional screening methods.
1279751
Fast lossless multi-resolution motion estimation for scalable wavelet video coding
In this paper, we propose a fast lossless multi-resolution motion estimation algorithm in shift-invariant wavelet domain by using wavelet matching error characteristic based partial distortion elimination (MR-WMEC-PDE). Due to its multi-resolution nature, the proposed approach can be applied to scalable video coding. The proposed algorithm can achieve the same estimate accuracy as full search algorithm (FSA), while needing much less computation requirement than FSA