Adaptive Noise Reduction for Engineering Drawings Based on Primitives and Noise Assessment
In this paper, a novel adaptive noise reduction method for engineering drawings is proposed based on the assessment of both primitives and noise. Unlike the current approaches, our method takes into account the special features of engineering drawings and assesses the characteristics of primitives and noise such that adaptive procedures and parameters are applied for noise reduction. For this purpose, we first analyze and categorize various types of noise in engineering drawings. The algorithms for average linewidth assessment, noise distribution assessment and noise level assessment are then proposed. These three assessments are combined to describe the features of the noise of each individual engineering drawing. Finally, median filters and morphological filters, which can adjust their template size and structural element adaptively according to different noise level and type, are used for adaptive noise reduction. Preliminary experimental results show that our approach is effective for noise reduction of engineering drawings.

title: A Pixel-level Statistical Structural Descriptor for Shape Measure and Recognition
abstract: A novel shape descriptor based on the histogram matrix of pixel-level structural features is presented. First, length ratios and angles between the centroid and contour points of a shape are calculated as two structural attributes. Then, the attributes are combined to construct a new histogram matrix in the feature space statistically. The proposed shape descriptor can measure circularity, smoothness, and symmetry of shapes, and be used to recognize shapes. Experimental results demonstrate the effectiveness of our method.

title: Extraction of Text Objects in Video Documents: Recent Progress
abstract: Text extraction in video documents, as an important research field of content-based information indexing and retrieval, has been developing rapidly since 1990s. This has led to much progress in text extraction, performance evaluation, and related applications. By reviewing the approaches proposed during the past five years, this paper introduces the progress made in this area and discusses promising directions for future research.

title: A PDA-based sign translator
abstract: We propose an effective approach for a PDA-based sign system and present the sign translator. Its main functions include three parts: detection, recognition and translation. Automatic detection and recognition of text in natural scenes is a prerequisite for the automatic sign translator. In order to make the system robust for text detection in various natural scenes, the detection approach efficiently embeds multi-resolution, adaptive search in a hierarchical framework with different emphases at each layer. We also introduce an intensity-based OCR method to recognize characters in various fonts and lighting conditions, where we employ the Gabor transform to obtain local features, and LDA for selection and classification of features. The recognition rate is 92.4% for the testing set obtained from the natural sign. A sign is different from the normal used sentence. It is brief with a lot of abbreviations and place nouns. We only briefly introduce a rule-based place name translation. We have integrated all these functions in a PDA, which can capture sign images, auto segment and recognize the Chinese sign, and translate it into English.

title: The nature of knowledge and its influence on knowledge sharing practice: experiences from building the MACROS system
abstract: This study investigates how the interactive influences of the nature of knowledge and multiple organizational and technological factors - trust, leadership, incentives and issues, group size and variety, implementation strategy, and technology - facilitated and/or impeded the knowledge sharing processes. Using a case study approach, the research focuses on the modifying effects of four characteristics of knowledge- codifiability, context-embeddedness, practice-embeddedness, and dynamics- on the processes and outcomes of knowledge sharing in a case of building the multi-purpose access for customer relations & operational support (MACROS) system involving multiple organizations, divisions, and geographically separated offices. The case results suggest that modifying effects occurred along at least three dimensions- codifiability, context-embeddedness, and practice-embeddedness. The levels of codifiability appeared to dictate the implementation strategy; reduced context-embeddedness allowed for more effective group coordination; reduced context-embeddedness also enhanced trust; codified knowledge is more effective than uncodified knowledge in demonstrating concrete incentives; and technology interacts with context-embeddedness and practice-embeddedness. The results of this study have theoretical and practical implications for a larger set of problems encountered in sizable organizations. More specifically, even though the relevance of the nature of knowledge has been widely acknowledged by I. Nonaka, et. al. (2001), it is not always clear how it comes into play. This study conceptualized the nature of knowledge as a modifying variable, and the results provide a new and more comprehensive framework for investigating the relevance of the nature of knowledge in knowledge management research.

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: ROI Based Natural Image Retrieval Using Color and Texture Feature
abstract: Region of interest(ROI) plays an important role in image analysis. In this paper, an efficient approach for content based image retrieval combining both color and texture features using three ROIs is proposed. Firstly, segment image to three parts using K-means algorithm. Secondly, select three ROIs from the three parts and then extract color features and texture features of ROIs. The similarity of two images will be determined by the similarities between pairs of ROIs. The experimental results demonstrate that the proposed method is encouraging with a successful retrieval rate.

title: Robust Controller for Networked Control Systems Induced Noise and Long Transmission Delay