Bor-Tow Chen

Measuring of a three-dimensional surface by use of a spatial distance computation

The correspondence problem of two captured images, which are obtained by projecting a structured light on the measuring surface, are explored for when three-dimensional information of a given surface is needed. In our system the constraint that codifies the pattern projected on the surface has been simplified by using a random speckle pattern, thus the correspondence problem is reduced tolocal matching between two captured images and solved by a spatial distance computation technique. The performance of our approach, which includes a disparity error analysis, a search range suggestion, and a disparity gradient limit, are investigated and discussed. Some parameters, such as percentile constraint, sampling interval, and subpixel compensation proper for use in this approach are suggested. Experiments have shown the feasibility of the proposed method.

Automatic histogram specification based on fuzzy set operations for image enhancement

An automatic histogram specification method is proposed for image enhancement. Parameterized fuzzy number (PFN) is adopted for the representation of image histogram. The desired histogram PFN is automatically constructed by the fuzzy addition of the tuning PFN and the original one. The tuning PFN is implied from the fuzzy inference rules. The mapping function is decided by the relations between the desired PFN and the original one. The effectual results are demonstrated by the mapping functions which meet the image enhancement requirements. The performance and effectiveness are shown by the analysis and the resultant image in comparison with other methods. >

A parameterized fuzzy processor and its applications

Abstract In this paper, a parameterized fuzzy processor (PFP) is presented based on a designed fuzzy instruction set of the parameterized fuzzy number (PFN). This PFN is presented by some parameters of the universe of the discourse instead of a series of the membership grades. The algorithms of these instructions are based on the parameter operations to implement the fuzzy arithmetics and the fuzzy reasoning methods. The instruction set supports the versatility of the fuzzy information, e.g., fuzzy arithmetic operations, inference operations, fuzzy logic operations, data translations and data exchangements. Based upon these, the characteristics of the PFN are discussed, and the architecture of the PFP outlined is constructed in this paper and its processing time is saved due to the adaptation of the parameterized fuzzy number (PFN). To evaluate the performance of PFN instructions and PFP structure, two experiments are presented. One is the speed performance evaluated for the PFN to compare with the discrete fuzzy number (DFN). The other is the confirmation of the feasibility and the capability of the instructions, which is demonstrated by three examples relateld to human inference, intuitive control and decision-making.

Efficient fuzzy c-means clustering for image data

The clustering process can be quite slow when there is a large data set to be clustered. We investigate four efficient fuzzy c-means clustering methods qFCMs, based on the quad-tree application to multispectral image feature compression and/or an aggregation process to reduce the number of exemplars for image analysis. An image is first partitioned into multiresolution blocks with variable size to extract the representative ones by homogeneity criteria. The blocks can be represented by a mean or fuzzy number to represent the image information. The first algorithm qFCMb is performed by applying only the representative blocks to a weighted FCM, which can speed up the clustering. To further improve the clustering efficiency, the reduction is done by aggregating similar examples and using a weighted exemplar in the clustering process (qFCMba). Based on the same processes used in qFCMb and qFCMba, nonhomogeneous regions including pixel information can also be supplemented to refine the clustering results, which are termed qFCMp and qFCMpa, respectively. Because of the merit of higher efficiency with the aggregation process, we recommend qFCMba and qFCMpa. A set of 14 images is used for experiments, comparison, and discussion. Performances are reported by the mean reduction rate, speedup, mean correspondence rate, and root mean square error. Results show that the mean reduction rate of both qFCMba and qFCMpa can be as high as 98% reduction in sample size. Average speedups of as much as 40 to 150 times (100 to 200 times) a traditional implementation FCM are obtained using qFCMpa (qFCMba), while producing partitions that are equivalent to those produced by FCM. On the measure of root mean square error, qFCMba is the better choice, as indicated in the experiment of clustering a noisy image.

Color image analysis using fuzzy set theory

An application of fuzzy set theory to the color image analysis is presented in this paper. It is developed to inference the weather state from a color image. For a color image, its RGB components are first converted into HSI components. For each component, a 3-layer quadtree is created for image analysis. Then the histogram of each block image from the top layer to bottom layer is computed. The histogram is further converted into a membership function by using the scheme of a 6-parameter fuzzy number. The fuzzy inference for the given image is thus achieved by using the generated membership functions.

Performance evaluation of a parameterized fuzzy processor (PFP)

Abstract In the human-based world, the general-purpose and high-speed fuzzy processor which supports more functions and capabilities plays a very important role. A parameterized fuzzy processor (PFP) has been proposed earlier (B.-T. Chen et al., 1993) to demonstrate its structure and applications. In this paper, the general performance of the PFP will be shown in detail by a series of analyzing results. First, fuzzy data presentation adopted in the PFP is evaluated by the proposed criteria and compared with the other presentations. According to the versatile data presentations, the general-purpose operations are evaluated by the computation order and run time. Second, the emphasized characteristics of PFP operations possess the feasibility of parallel and pipelined processing. The designed circuit and execution cycles are confirmed in a simulation environment. Finally, the fuzzy applications extendable by the general-purpose PFP are shown by the solvable operations. Based on the PFP, a processing model for human-based problems is proposed to analyze the fuzzy applications. A practical application is proposed to demonstrate the capability of the PFP.

A solution of correspondence problem for measuring 3D surface

This paper deals with the correspondence problem of two grabbed images, obtained by projecting a structured light on the measuring surface, when 3D information of a given surface is needed. In our system, the constraint that codifies the pattern projected on the surface has been simplified by using a random speckle pattern, thus the correspondence problem is reduced to the local matching between two grabbed images and solved by a spatial distance computation technique. Experiments have shown the feasibility of the proposed method.

Modeling and simulation of a parameterized fuzzy processor

A fuzzy instruction set of a parameterized fuzzy number is proposed. The instruction set supports the versatility of the fuzzy information. An architecture of the fuzzy processor is also outlined. Then, to confirm the capability of the instructions, examples concerning human inference intuitive control, and decision-making are demonstrated. The results described are satisfactory; they confirm that this system is suitable for fuzzy information processing.<<ETX>>

Three-Dimensional Digital Colour Camera

Digital colour camera now has been a popular consumer equipment, has widely used in our daily life, and is highly suited for the next generation of cellular phones, personal digital assistants and other portable communication devices. The main applications of digital colour camera are used to take a digital picture for personal use, picture editing and desktop publishing, high-quality printing, and image processing for advanced academic research. The digital picture is a two-dimensional (2D) form with three-colour components (Red, Green, Blue). The most of efforts for a digital camera producer are focusing on the improvements of image compression, image quality, image resolution, and optical/ digital zooming. However, consider the wide field of computer vision, the depth for a captured object may be another very useful and helpful information, such as surface measurement, virtual reality, object modelling and animation, it will be valuable if the depth information can be obtained while a picture is being captured. In other words, three-dimensional (3D) imaging devices promise to open a very wide variety of applications, particularly, those involving a need to know the precise 3D shape of the human body, e.g. e-commerce (clothing), medicine (assessment, diagnosis), anthropometry (vehicle design), postproduction (virtual actors) and industrial design (workspace design) (Siebert & Marshall, 2000). To achieve this significant function, a novel 3-D digital colour camera has been successfully developed by Industrial Technology Research Institute, Opto Electronics & Systems Laboratories (ITRI-OES), in Taiwan. In this article, the previous works, algorithms, structure of our 3D digital colour camera, and 3D results, will be briefly presented. To obtain 3D information of a given object, the approach may be considered in between a passive scheme and an active scheme. The widely known passive scheme is stereovision, which is useful to measure surfaces with well-defined boundary edges and vertexes. An algorithm to recognize singular points may be used to solve the problem of correspondence between points on both image planes. However the traditional stereoscopic system becomes rather inefficient to measure continuous surfaces, where there are not many reference points. It has also several problems in textural surfaces or in surfaces with lots of discontinuities. Under such an environment, the abundance of reference points can produce

Design of a parameterized fuzzy processor and its applications

The design of a parameterized fuzzy processor (PFP) which plays the role of a man-machine interface is described. The set of instructions is designed for supporting the versatility of the fuzzy information. The architecture of the PFP is also presented. Then, some applications of human inference and intuitive control are presented which show that the PFP is feasible.<<ETX>>