A process of mixing viscous fluids, such as oil-based paints is applied to generate marble patterns. It is difficult to get the exact flow function of the viscous fluid, then we express the flow in terms of velocity vectors derived from simplified flow phenomena, in which the viscous liquid is supposed to be a collection of finite liquid elements. The position change of each element is calculated as the function of time and several examples of the obtained marble patterns are illustrated.

This paper presents a new template matching method based on marker-controlled watershed segmentation (TMCWS). It is applied to recognize numbers on special metal plates in production lines where traditional image recognition methods do not work well. TMCWS is a shape based matching method that uses different pattern images and their corresponding marker images as probes to explore a gradient space of an unknown image to determine which pattern best matches a target object in it. Different from other matching algorithms, TMCWS firstly creates a marker image for each pattern, and then takes both the pattern image and its corresponding marker image as a template window and shifts this window across a gradient space pixel by pixel to do a search. At each position, the marker image is used to try to extract the contour of the target object with the help of marker-controlled watershed segmentation, and the pattern image is employed to evaluate the extracted shape in each trial. All of the pattern images and their corresponding marker images are tried and the pattern that best matches the target object is the recognition result. TMCWS contains shape extraction procedures and it is a high-level template matching method. Experiments are performed with this method on nearly 400 images of metal plates and the test results show its effectiveness in recognizing numbers in noisy images.

A new method for interpolating boundary function values and first derivatives of a triangle is presented. This method has a relatively simple construction and involves no compatibility constraints. The polynomial precision set of the interpolation function constructed includes all the cubic polynomial and less. The testing results show that the surface produced by the proposed method is better than the ones by weighted combination schemes in both of the fairness and preciseness.

A new recognition method for partially occluded two dimensional objects is described in the present paper. Several vectors named PSVs, Partial Shape Vectors, are proposed as local features of an object and used for recognition. Two dimensional objects similar to a given model are extracted by this method. PSVs denote turning angles at an arbitrary point of the contour line of an object. In the recognition process, PSVs of each picture point in the given image are obtained and compared with PSVs of feature points which were set on the model. From coordinate values of the candidates for the feature points, objects similar to the model are extracted.

It is described that an interactive method of generating easily a pseudo-stereo pair from a two dimensional manually drawn line figure, which has not three dimensional data.

A genetic method to generate a neural network which has both structure and connection weights adequate for a given task is proposed. A neural network having arbitrary connections is regarded as a virtual living thing which has genes representing its connections among neural units. Effectiveness of the network is estimated from its time sequential input and output signals. Excellent individuals, namely appropriate neural networks, are generated through generation iterations. The basic principle of the method and its applications are described. As an example of evolution from randomly generated networks to feedforward networks, an XOR problem is dealt with, and an action control problem is used for making networks containing feedback and mutual connections. The proposed method is available for designing a neural network whose adequate structure is unknown.