A New FCM-Based Algorithm of Hydrophobic Image Segmentation

title: An Improved Fuzzy Image Enhancement Algorithm
abstract: An effective method for fuzzy image enhancement was presented by Russo, which was controlled by tuning of one parameter. The fixed parameter was used for the entire image resulting in over blurring or sharpening of image features in some parts of the image. On the basis of these, in this paper, we applied Russo's algorithm on different kinds of noise and proposed an efficient method to obtain the parameter values adaptively. Firstly, each pixel went through a phase of smoothing and then followed by a phase of combining smoothing and sharpening; Secondly, to effectively enhance image, each pixel local feature was adaptively assigned different parameter values by evaluating pixel local features through a fuzzy membership function; Finally, compared with Russopsilas method and other methods, experimental results indicated that the proposed method could achieve better performance than traditional methods for the enhancement of images corrupted with impulse and Gaussian noise.

title: Dynamic Terrain LOD with Region Preservation in 3D Game Engine
abstract: In the outdoor 3D game, the terrain can be modified because of interaction. This brings two new complexities to render terrain in 3D game. The first lies in the real-time visualization of dynamic terrain, and the second is that the modified terrain surface need to be preserved. We present an algorithm for dynamic terrain LOD(DT LOD) with preserving region in 3D game engine. The algorithm uses a DAG to represent dependency relationship of vertices which split triangles, and employs an active vertices set to update triangles in two consecutive frames for improving rendering performance. The region LOD can be constructed according to the view direction and the distance between the viewpoint and regions. The results of experiments show that our algorithm has a effective performance during rendering terrain.

title: Index Support for Visualizing Large, Distributed, High-Dimension Data Sets

title: Motion segmentation of multiple translating objects from line correspondences
abstract: This paper presents an analytic approach to motion segmentation of multiple translating objects from line correspondences in three perspective views. The basic idea of our algorithm is to view the estimation of multiple translational motions as the estimation of a single, though more complex, multibody motion model that is then factored into the original models by polynomial differentiation. Experimental results on synthetic and real scenes are presented.

title: Interweave Neural Networks with Evolutionary Algorithms, Cellular Computing, Bayesian Learning and Ensemble Learning
abstract: A neural networks are able to give solutions to complex problems in business intelligence and financial engineering due to their nonlinear processing. This paper consists of a survey of various business intelligence and financial engineering and so on applications based on the neural networks, and also a summary of the recent techniques such as still evolutionary algorithms, cellular computing, Bayesian learning and ensemble learning. The neural networks can be powerful tools in several fields of business intelligence and financial engineering. It can be concluded that, the future of neural networks lies in their use in conjunction with other advanced technologies.

title: The Predictive Control of Sintering Temperature in Rotary Kiln Based on Image Feedback and Soft Computing
abstract: The sintering temperature in rotary kiln is measured through image processing algorithm as feedback of its predictive control. The predictive model based on radial basis function (RBF) network is designed by the image and other process data optimized by genetic algorithm. The final results of application at an alumina sintering kiln show that this intelligent predictive control strategy can achieve higher stability in normal condition.