Page segmentation using minimum homogeneity algorithm and adaptive mathematical morphology

Document layout analysis or page segmentation is the task of decomposing document images into many different regions such as texts, images, separators, and tables. It is still a challenging problem due to the variety of document layouts. In this paper, we propose a novel hybrid method, which includes three main stages to deal with this problem. In the first stage, the text and non-text elements are classified by using minimum homogeneity algorithm. This method is the combination of connected component analysis and multilevel homogeneity structure. Then, in the second stage, a new homogeneity structure is combined with an adaptive mathematical morphology in the text document to get a set of text regions. Besides, on the non-text document, further classification of non-text elements is applied to get separator regions, table regions, image regions, etc. The final stage, in refinement region and noise detection process, all regions both in the text document and non-text document are refined to eliminate noises and get the geometric layout of each region. The proposed method has been tested with the dataset of ICDAR2009 page segmentation competition and many other databases with different languages. The results of these tests showed that our proposed method achieves a higher accuracy compared to other methods. This proves the effectiveness and superiority of our method.     

Online recognition of sketched arrow-connected diagrams

We introduce a new, online, stroke-based recognition system for hand-drawn diagrams which belong to a group of documents with an explicit structure obvious to humans but only loosely defined from the machine point of view. We propose a model for recognition by selection of symbol candidates, based on evaluation of relations between candidates using a set of predicates. It is suitable for simpler structures where the relations are explicitly given by symbols, arrows in the case of diagrams. Knowledge of a specific diagram domain is used—the two domains are flowcharts and finite automata. Although the individual pipeline steps are tailored for these, the system can readily be adapted for other domains. Our entire diagram recognition pipeline is outlined. Its core parts are text/non-text separation, symbol segmentation, their classification and structural analysis. Individual parts have been published by the authors previously and so are described briefly and referenced. Thorough evaluation on benchmark databases shows the accuracy of the system reaches the state of the art and is ready for practical use. The paper brings several contributions: (a) the entire system and its state-of-the-art performance; (b) the methodology exploring document structure when it is loosely defined; (c) the thorough experimental evaluation; (d) the new annotated database for online sketched flowcharts and finite automata diagrams.     

Review of some advances and applications in real-time high-speed vision: Our views and experiences

The frame rate of conventional vision systems is restricted to the video signal formats(e.g., NTSC 30 fps and PAL 25 fps that are designed on the basis of the characteristics of the human eye, which implies that the processing speed of these systems i limited to the recognition speed of the human eye. However, there is a strong demand for real-time high-speed vision sensors in many application fields, such as factory automation, biomedicine, and robotics, where high-speed operations are carried out. Thes high-speed operations can be tracked and inspected by using high-speed vision systems with intelligent sensors that work at hundred of Hertz or more, especially when the operation is difficult to observe with the human eye. This paper reviews advances in developing real-time high speed vision systems and their applications in various fields, such as intelligent logging systems, vibration dynamic sensing, vision-based mechanical control, three-dimensional measurement/automated visual inspection, vision-based human interface and biomedical applications.     

Robust face recognition against expressions and partial occlusions

Facial features under variant-expressions and partial occlusions could have degrading effect on overall face recognition performance. As a solution, we suggest that the contribution of these features on final classification should be determined. In order to represent facial features contribution according to their variations, we propose a feature selection process that describes facial features as local independent component analysis(ICA) features. These local features are acquired using locally lateral subspace(LLS) strategy.Then, through linear discriminant analysis(LDA) we investigate the intraclass and interclass representation of each local ICA feature and express each feature s contribution via a weighting process. Using these weights, we define the contribution of each feature at local classifier level. In order to recognize faces under single sample constraint, we implement LLS strategy on locally linear embedding(LLE) along with the proposed feature selection. Additionally, we highlight the efficiency of the implementation of LLS strategy. The overall accuracy achieved by our approach on datasets with different facial expressions and partial occlusions such as AR, JAFFE,FERET and CK+ is 90.70%. We present together in this paper survey results on face recognition performance and physiological feature selection performed by human subjects.     

Advances in vehicular ad-hoc networks (VANETs): Challenges and road-map for future development

Recent advances in wireless communication technologies and auto-mobile industry have triggered a significant research interest in the field of vehicular ad-hoc networks (VANETs) over the past few years. A vehicular network consists of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications supported by wireless access technologies such as IEEE 802.11p. This innovation in wireless communication has been envisaged to improve road safety and motor traffic efficiency in near future through the development of intelligent transportation system (ITS). Hence, governments, auto-mobile industries and academia are heavily partnering through several ongoing research projects to establish standards for VANETs. The typical set of VANET application areas, such as vehicle collision warning and traffic information dissemination have made VANET an interesting field of mobile wireless communication. This paper provides an overview on current research state, challenges, potentials of VANETs as well as the ways forward to achieving the long awaited ITS.     

Set-based particle swarm optimization with status memory for knapsack problem

Set-based particle swarm optimization (S-PSO) operates on discrete space. S-PSO can solve combinatorial optimization problem with high quality and is successful to apply to the large-scale problem. In S-PSO, a velocity is a set with possibility and a position is a candidate solution. In this paper, we present a novel algorithm of set-based particle swarm optimization with status memory (S-PSOSM) to decide the position based on the previous position for solving knapsack problem. Some operators are redefined for S-PSOSM. S-PSOSM is a simple algorithm because the state of probability reduces. In addition, the weight of S-PSOSM is discussed. S-PSOSM shows high qualities in experimental results.     

Study on stiffness visualization and safety control based on will-consensus building for tele-palpation robot system

This paper proposes a method for visualizing the stiffness of a soft object in a palpation-support information system by the teleoperation of a robot hand. It is important that a palpation system display a body’s shape and stiffness. In our method, the stiffness of the contact area between the soft object and the robot finger is estimated by a recursive least-squares method with forgetting factor that uses an impedance dynamics model. With the estimated stiffness and direction of contact force, we calculate the scalar parameter for visualization of stiffness. Moreover, we propose a safety control method for the palpation system, which is part of a tele-control method based on will-consensus building. The system configuration, estimated algorithm, and experimental results are presented.     

Agent-based modeling of collaborative interaction in ubiquitous learning environment using local dynamic behavior

This paper focuses on modeling collaborative interaction in Ubiquitous Learning Environment (ULE) based on the assumption that the collaborative interaction can be perceived through interpersonal interactions, which can be described as local dynamic behaviors of the team. In this paper, the collaborative interaction is collected from the experiment with 50 students having 5 members per team. Then the collaborative interaction is coded with 16 participation shift (P-shifts) from 5 different types of turns including turn receiving, turn claiming, turn usurping, turn continuing, and turn noreturning to represent the participation status of each member. Three types of participation statuses used in this paper are the contributor, the target and the unaddressed recipient. Then the discovered local dynamic behavior is used for constructing the model by using agent-based modeling. The model consists of student agents working together according to the discovered behavior. Then, the constructed model is verified by comparing the actual behavior with the simulated behavior. Finally, the comparison result shows that the constructed model can reasonably be the model for modeling collaborative interaction in ULE.     

Parallelized fusion visualization system

The speed-up of supercomputers has increased the complexity of simulations. To analyze such kind of data, we believe that new types of visualization software are needed. Therefore, we have been developing a visualization system called “Fusion Visualization”, and the progresses were reported in the AROB 18th and 19th International Symposiums. We introduced the overall concept at the AROB 18th International Symposium, and then demonstrated a sample of flow visualization in a blood vessel in the AROB 19th International Symposium. To extend our system to enable the handling of larger data, we have implemented the proposed system on a parallelized visualization system; AVS/Express PCE (Parallel Cluster Edition). This paper describes the implementation and the benchmark results.     

New time-varying fuzzy sets based on a PSO midpoint of the universe of discourse

The paper presents a robust parallel distributed compensation(PDC) fuzzy controller for a nonlinear and certain system in continuous time described by the Takagi-Sugeno(T-S) fuzzy model. This controller is based on a new type of time-varying fuzzy sets(TVFS). These fuzzy sets are characterized by displacement of the kernels to the right or left of the universe of discourse, and they are directed by a well-defined criterion. In this work, we only focused on the movement of midpoint of the universe. The movements of this midpoint are optimized by particle swarm optimization(PSO) approach.