A new algorithm to preserve edges in image magnification is proposed. The algorithm is based on an inpainting technique: Blurry edges in the initially magnified image are erased using automatic edge detections, then the erased regions are filled with the filling priority guided by the watershed concept. The algorithm results in sharp patterns along the edges of the initial image, and the discontinuity across the edges is guaranteed. Experiments demonstrate that the algorithm is superior to some popular methods such as edge-directed interpolations and anisotropic diffusions.

Software maintenance effort estimation is essential for the success of software maintenance process. In the past decades, many methods have been proposed for maintenance effort estimation. However, most existing estimation methods only produce point predictions. Due to the inherent uncertainties and complexities in the maintenance process, the accurate point estimates are often obtained with great difficulties. Therefore some prior studies have been focusing on probabilistic predictions. Analogy Based Estimation (ABE) is one popular point estimation technique. This method is widely accepted due to its conceptual simplicity and empirical competitiveness. However, there is still a lack of probabilistic framework for ABE model. In this study, we first propose a probabilistic framework of ABE (PABE). The predictive PABE is obtained by integrating over its parameter k number of nearest neighbors via Bayesian inference. In addition, PABE is validated on four maintenance datasets with comparisons against other established effort estimation techniques. The promising results show that PABE could largely improve the point estimations of ABE and achieve quality probabilistic predictions.

The objective of view planning in a visual sensing system is to make task-directed decisions for optimal sensing pose selection. The primary focus of the research described in this paper is to propose a new method for creating a complete model of free-form surface object from multiple range images acquired by a scan sensor at different space poses. Using the view sphere to limit the number of possible sensor positions, the candidates for the next-best-view (NBV) position are easily determined by detecting and measuring occlusions to the camera's view in an image. Ultimately, the candidate which obtains maximum the known partial modeling boundary integral value of the vector fields is selected as the next-best-view position. We also present a self-termination criterion for judging the completion condition in the measurement and reconstruction process. The termination condition is derived based on changes in the volume computed from two successive viewpoints. The experimental results show that the method is effective in practical implementation

In this paper, we present a new method for automatic recalibration of the relative pose in a structured light system by a single image of planar surface. Assuming that the intrinsic parameters of the camera and the projector are known from initial calibration, we show that their relative orientation and position can be determined automatically from four projection correspondences in an image and a projection plane. In this method, two steps are taken to solve the pose problem. The advantages are that not only the analytic solutions can be obtained easily but also an over constraint system is constructed in each step to increase the robustness. Some computer simulations and real data experiments have been carried out to validate our method

This paper presents a method for automatic sensor placement for model-based robot vision. In such a vision system, the sensor often needs to be moved from one pose to another around the object to observe all features of interest. This allows multiple three-dimensional (3-D) images to be taken from different vantage viewpoints. The task involves determination of the optimal sensor placements and a shortest path through these viewpoints. During the sensor planning, object features are resampled as individual points attached with surface normals. The optimal sensor placement graph is achieved by a genetic algorithm in which a min-max criterion is used for the evaluation. A shortest path is determined by Christofides algorithm. A Viewpoint Planner is developed to generate the sensor placement plan. It includes many functions, such as 3-D animation of the object geometry, sensor specification, initialization of the viewpoint number and their distribution, viewpoint evolution, shortest path computation, scene simulation of a specific viewpoint, parameter amendment. Experiments are also carried out on a real robot vision system to demonstrate the effectiveness of the proposed method.

In this paper we present an uncertainty-driven viewpoint planning approach for measurement and digitalization of free form 3D objects. The object surface is first decomposed into a number of cross section curves, and each curve is reconstructed by a closed B-spline curve. Then, we analyze the uncertainty of the B-spline model. Based on this, we predict the information gain for each cross section curve for candidate views. After predicting the information again of all the B-spline models into the view space. The viewpoint that contains maximal information gain about the object is selected as the Next Best View. Experimental results are given in the digitization and reconstruction of freeform objects using our view planning method.

In this paper, an unsupervised segmentation method using clustering is presented for color images. We propose to use a neural network based approach to automatic feature selection to achieve adaptive segmentation of color images. With a self-organizing feature map (SOFM), multiple color features can be analyzed, and the useful feature sequence (feature vector) can then be determined. The encoded feature vector is used in the final segmentation using fuzzy clustering. The proposed method has been applied in segmenting different types of color images, and the experimental results show that it outperforms the classical clustering method. Our study shows that the feature encoding approach offers great promise in automating and optimizing the segmentation of color images.

This paper describes the work of an on-going project investigating the incorporation of physics-based modeling for simulating dynamic interactions in robotic aided manipulations. The research aims at achieving better simulation of robot behaviors in real situations, making it a useful tool for off-line programming. By allowing manipulation strategy simulation and performance visualization of a designed operation to be carried out within a virtual environment, the system will be a valuable tool for handling strategy design, testing, modification, and optimization without fear of damaging the physical systems. As an environment for demonstrating tasks to robots, the systems will also be a useful platform for robot teaching and training. The system has particular promise in flexible assembly where it is more economical to perform the reconfiguration of a work cell and to generate or modify handling strategies for new tasks without having to shut down the real system. This paper reports the initial work carried out with the preliminary results given.

Proximity sensing and direct robot end effector position feedback are essential for real time sensor based control to enhance the perfor- mance of robot systems. The true values of the robot end velocity play a very important role in this task. Existing methods dealing with the prob- lem, however, are not valid or feasible under cer- tain conditions. A new measurement and filtering technique is proposed to derive the end velocity more reliably for a robot with highly uncertain vi- brational modes. The effectiveness of the approach is verified by both simulation and experiment.

Application of fuzzy algorithms in a microprocessor based servomotor controller that requires faster and more accurate response than other industrial processes is discussed. The performance proportional-integral-derivative, model reference adaptive and fuzzy controllers is compared in terms of steady-state error, settling time and response time. The limitation of the fuzzy control algorithms is ascertained.>