14683359
Fast initialization of level set method and an improvement to Chan-Vese model
The initialization is an important step in the level set method. However, it is a computational time-consuming step. In order to speed up the level set evolution procedures, we first introduce a new initialization algorithm based on the vector distance transform, which propagates a vector with a position of the nearest object pixel instead of the scalar distance. A new sign map labeling method, based on the flood fill, is proposed to distinguish the inside and outside of the 2D closed active contour. The active contour model proposed by Chan and Vese (Chan and Vese, 2001) can detect object whose boundaries are not necessarily defined by gradient. Our additional contribution to this paper is to present a further improvement to C-V model by replacing /spl delta/(/spl Phi/) with |/spl nabla//spl Phi/| to gain the global optimization. Finally, we illustrate the efficiency and performance of the proposed model by experimental results.
18268847
Interactive model identification for nonholonomic cart pushed by a mobile manipulator
A model identification method for unknown environments has been developed. By the interactions between a mobile manipulator and the unknown object, a nonholonomic cart, sensory information has been collected to estimate the model parameters of the cart, which are used to control the cart. Since the raw data are contaminated by noise they can not be modeled statistically, a wavelet based least square method is proposed to estimate these parameters for the cart. The raw signal has been decomposed into a certain bandwidth to generate a series of new signals, which are used to estimate the parameters. The new signal, which has the minimal estimation residual in least square sense is adopted as the best estimation. The error convergence of the estimation approach is given. The experimental results indicate that the estimation accuracy can be significantly improved by the use of the proposed method.
6883825
Integrated Task Planning and Control for Mobile Manipulators
In this paper we present an approach to decoupled force/position control of the end-effector along the same direction for redundant robots, and an approach to nonholonomic cart pushing with mobile manipulators. The mobile manipulator is considered as a redundant robot, and a unified dynamic model for an integrated mobile platform and on-board manipulator is developed. The dynamic model is decoupled and linearized using the nonlinear feedback technique in a unified frame. Combining the event-based planning and control method with singularity analysis of the robot arm, a task level action controller is designed and an online kinematic redundancy resolution scheme is developed. The system is stable during normal operation as well as at the occurrence of unexpected obstacles. In addition, explicit force/position control along the same task direction for redundant robots is proposed. The kinematic redundancy of mobile manipulators enables independent control of force and position along the same task directions. To verify the decoupled force/postion scheme, an integrated task planning and control approach is further proposed for the mobile manipulator to complete complicated tasks by regulating its output force. A cart pushing task, which requires both force and position control along the same task direction, is discussed. The cart manipulation task fully integrates trajectory and force planning of the cart, and planning and control of the mobile manipulators. The approaches have been tested on a mobile manipulator consisting of a Nomadic XR4000 and a Puma 560 robot arm. The experimental results demonstrate the efficacy of the approach for the mobile manipulation of a nonholonomic cart.
32026454
Color-texture image segmentation by integrating directional operators into JSEG method
We presented a new color-texture image segmentation method that combined directional operators and the JSEG (J measure based SEGmentation) algorithm. In particular, two major contributions were set forth in this paper. (1) The two measures defined in JSEG and HSEG (H measure based SEGmentation) were discussed respectively and then we found the over-segmentation problem of JSEG could be attributed partly to the absence of color discontinuity in the J measure. Moreover, we have also proven in essence the H measure is isotropic operators for edge detection in images. (2) A new measure was proposed by integrating directional operators into the J measure, on which our segmentation method was based. The new segmentation method took account of both textural homogeneity and color discontinuity in local regions. Performance improvement due to the proposed modification was demonstrated on a variety of real color images.
41292415
Randomness, Stochasticity and Approximations
Polynomial time unsafe approximations for intractable sets were introduced by Meyer and Paterson [9] and Yesha [19], respectively. The question of which sets have optimal unsafe approximations has been investigated extensively; see, e.g., [1], [5], [15], and [17]. Recently, Wang [15], [17] showed that polynomial time random sets are neither optimally unsafe approximable nor Δ -levelable. In this paper we show that: (1) There exists a polynomial time stochastic set in the exponential time complexity class which has an optimal unsafe approximation. (2) There exists a polynomial time stochastic set in the exponential time complexity class which is Δ -levelable. The above two results answer a question asked by Ambos-Spies and Lutz [2]: What kind of natural complexity property can be characterized by p -randomness but not by p -stochasticity? Our above results also extend Ville's [13] historical result. The proof of our first result shows that, for Ville's stochastic sequence, we can find an optimal prediction function f such that we will never lose our own money betting according to f (except the money we have earned), that is to say, if at the beginning we have only $1 and we always bet $1 that the next selected bit is 1 , then we always have enough money to bet on the next bit. Our second result shows that there is a stochastic sequence for which there is a betting strategy f such that we will never lose our own money betting according to f (except the money we have earned), but there is no such optimal betting strategy. That is to say, for any such betting strategy, we can find another betting strategy which could be used to make money more quickly.
793367
3D Brain surface matching based on geodesics and local geometry
The non-rigid registration of surfaces is a complex and difficult task for which there are many important applications, such as comparing shape between deformable objects and comparing associated function. This paper presents a new approach for brain surface matching by determining the correspondence of 3D point sets between pairs of surfaces. The algorithm is based on shape using a combination of geodesic distance and surface curvature. There are two major procedures involved. An initial sparse set of corresponding points is first generated by matching local geometrical features. Geodesic distance interpolation is then employed hierarchically in order to capture the complex surface. By this scheme, surface correspondence and triangulation are computed simultaneously. Experiments applied to human cerebral cortical surfaces are shown to evaluate the approach. It is shown that the proposed method performs well for both surface matching and surface shape recovery.
3032688
Statistical Identification of Key Phrases for Text Classification
Algorithms for text classification generally involve two stages, the first of which aims to identify textual elements (words and/or phrases) that may be relevant to the classification process. This stage often involves an analysis of the text that is both language-specific and possibly domain-specific, and may also be computationally costly. In this paper we examine a number of alternative keyword-generation methods and phrase-construction strategies that identify key words and phrases by simple, language-independent statistical properties. We present results that demonstrate that these methods can produce good classification accuracy, with the best results being obtained using a phrase-based approach.
15617422
R*-Histograms: efficient representation of spatial relations between objects of arbitrary topology
Representation of relative spatial relations between objects is often required in many multimedia database applications because spatial relations between objects in an image convey important information about the image. Quantitative representation of spatial relations taking into account shape, size, orientation and distance is often required. The R-Histogram is such a quantitative representation of spatial relations between two objects. However, this method only considers pixels on the object boundary, assuming that the objects are homeomorphic to a 2-ball. For objects with more complicated topology, we propose in this paper the R*-Histogram, a new extension to the R-Histogram. The R*-Histogram generalizes the R-Histogram by taking into account all the pixels in the objects. We also introduce an efficient O(kN log N) time algorithm to compute the R*-Histogram, which is asymptotically faster than the original O(N<sup>2</sup>) time algorithm for the R-Histogram even when k=O(n). Here, N=n<sup>2</sup> denotes the number of pixels in the processed n x n image and k is the number of different directions considered. The effectiveness of the R*-Histogram is evaluated empirically with a Query By Example (QBE) system on a database of 2000 synthetic images containing objects with complicated shape and topology. Experiments have shown that the similarly search results match human intuition very well.