Hwang-Kyu Yang

Frame segmentation used MLP-based X-Y recursive for mobile cartoon content

With rapid growth of the mobile industry, the limitation of small screen mobile is attracting a lot of researchers attention for transforming on/off-line contents into mobile contents. Frame segmentation for limited mobile browsers is the key point of off-line contents tranformation. The X-Y recursive cut algorithm has been widely used for frame segmentation in document analysis. However, this algorithm has drawbacks for cartoon images which have various image types and image with noises, especially the online cartoon contents obtain during scanning. In this paper, we propose a method to segment on/off-line cartoon contents into fitted frames for the mobile screen. This makes the x-y recursive cut algorithm difficult to find the exact cutting point. Therefore we use a method by combining two concepts: an X-Y recursive cut algorithm to extract candidate segmenting positions which shows a good performance on noises free contents, and Multi-Layer Perceptrons (MLP) concept use on candidate for verification. These methods can increase the accuracy of the frame segmentation and feasible to apply on various off-line cartoon images with frames.

Automatic mobile content conversion using semantic image analysis

An approach to knowledge-assisted semantic offline content re-authoring based on an automatic content conversion (ACC) ontology infrastructure is presented. Semantic concepts in the context are defined in ontology, text detection (e.g. connected component based), feature (e.g. texture homogeneity), feature parameter (e.g. texture model distribution), clustered feature (e.g. k-manes algorithm). We will show how the adaptation of the layout can facilitate browsing with mobile devices, especially small-screen mobile phones. In a second stage we address the topic of content personalization by providing a personalization scheme that is based on the ontology technology. Our experiment shows that the proposed ACC is more efficient than the existing methods in providing mobile comic contents.

An intelligent system for container image recognition using ART2-Based self-organizing supervised learning algorithm

This paper proposed an automatic recognition system of shipping container identifiers using fuzzy-based noise removal method and ART2-based self-organizing supervised learning algorithm. Generally, identifiers of a shipping container have a feature that the color of characters is black or white. Considering such a feature, in a container image, all areas excepting areas with black or white colors are regarded as noises, and areas of identifiers and noises are discriminated by using a fuzzy-based noise detection method. Noise areas are replaced with a mean pixel value of the whole image and areas of identifiers are extracted by applying the edge detection by Sobel masking operation and the vertical and horizontal block extraction in turn to the noise-removed image. Extracted areas are binarized by using the iteration binarization algorithm, and individual identifiers are extracted by applying 8-directional contour tracking method. This paper proposed an ART2-based self-organizing supervised learning algorithm for the identifier recognition, which creates nodes of the hidden layer by applying ART2 between the input and the hidden layers and improves the performance of learning by applying generalized delta learning and Delta-bar-Delta algorithm between the hidden and the output layers. Experiments using many images of shipping containers showed that the proposed identifier extraction method and the ART2-based self-organizing supervised learning algorithm are more improved compared with the methods previously proposed.

Mobile Education through Camera-Equipped Mobile Phones

In the container transportation, RFID and GSM/CDMA technology applied to monitor import and export goods, which will make sure the security of goods in transportation. In this paper, the container monitoring security infrastructure is provided, which is combined by national custom monitoring center, port monitoring center and vessel monitoring center, in the security infrastructure, the searching algorithm is discussed.This paper proposes augmented learning contents (ALC) that can supply learners with dynamic interactions using multimedia information by recognizing real images of off-line contents using mobile devices. The techniques employed allow children to rapidly gain access to a large repository of multimedia information through the use of a camera- equipped mobile phone. Especially, there are many usages of external marks (EM) on the off-line contents. To tackle this problem, a few researches use content-based image retrieval (CBIR) based on object colors to recognize real images with a simple computation. However, this has problems of low recognition rates and slows processing on mobile devices with low-resolution camera. There are three issues should be considered in this research field: (1) low recognition rates, (2) fast processing, and (3) rotation-size invariant. To solve drawbacks that use of the EM and difficulty of the color-based image retrieval (CoBIR) by means of a low-resolution camera-equipped mobile phone, we used for shape-based image retrieval (SBIR) system. The ALC can provide learners with quick and accurate on-line contents on off-line using mobile devices without limitations of space. Our aim was to establish whether or not this user interaction technique could be harnessed for education based applications targeted at young children.

Using Skeletonization and Shortest Skeleton Path Approach for Chinese Character Representation

This paper adopts skeletonization approach to represent Chinese character and uses the resulting written strokes for optimized matching. We use shortest path method that represented by end node pair and junction node pair in the character for matching. This strategy is improved from the original shortest skeleton path matching by introducing the junction node as an extra feature in order to be able to represent singularity, non-singularity and looping characteristics for Chinese characters. Our result shows an effective representation and matching of the character by skeletonization and shortest path method considering end nodes and junction nodes as matching strategy.

Recognition of concrete surface cracks using ART2-Based radial basis function neural network

In this paper, we proposed the image processing techniques for extracting the cracks in a concrete surface crack image and the ART2-based radial basis function neural network for recognizing the directions of the extracted cracks. The image processing techniques used are the closing operation of morphological techniques, the Sobel masking used to extract edges of the cracks, and the iterated binarization for acquiring the binarized image from the crack image. The cracks are extracted from the concrete surface image after applying two times of noise reduction to the binarized image. We proposed the method for automatically recognizing the directions (horizontal, vertical, -45 degree, 45 direction degree) of the cracks with the ART2-based RBF(Radial Basis Function) neural network. The proposed ART2-based RBF neural network applied ART2 to the learning between the input layer and the middle layer and the Delta learning method to the learning between the middle layer and the output layer. The experiments using real concrete crack images showed that the cracks in the concrete crack images were effectively extracted and the proposed ART2-based RBF neural network was effective in the recognition of the extracted cracks directions.

Effective image retrieval for the m-learning system

In this paper, we propose augmented learning contents (ALC) with the blended learning on mobile devices. It augments on-line contents by indexing the corresponding off-line contents using traditional pattern recognition method, which results in a minimize of labors for conversion. Among the pattern recognition method marker-based is one of most general approach. However it must reconstruct the off-line contents with pattern markers. To solve both drawbacks that use of the pattern markers and difficulty of the color-based image retrieval by means of a low-resolution PDA camera, we used for a shape-based system. CBIR based on object shapes is used instead of pattern markers to link off-line contents with on-line, and shapes are represented by a differential chain code with estimated new starting points to obtain rotation-invariant representation, which is suited to low computational resources of mobile devices. Consequently, the ALC can provide learner with a fast and accurate multimedia contents (video, audio, text) on static off-line contents using mobile devices without space limitation.