SVG (scalable vector graphics) has become the standard format for 2D graphics in HTML5. Although some image-to-SVG conversion systems had been proposed, the sizes of files they produced are still large. In [1], we proposed a new system to convert raster comic images into vector SVG files. The compression ratio is better than the previous methods. However, these methods do not process text in raster images. In this paper, we improve our system to recognize text elements in the comic and use these text elements to provide better compression and novel applications. The proposed method uses SCW (sliding concentric windows) and SVM (support vector machine) to identify text regions. Then, OCR (optical character recognition) is applied to recognize text elements in those regions. Instead of encoding the text regions as vectors, the text elements are embedded in the SVG file along with their coordinate values. Experimental results show that we can reduce the file sizes to about 52% of the original SVG files. Using these text elements, we can translate comics into other languages to provide multilingual services easily. Text/content-based image search can be supported efficiently. It can also provide a novel application system for story teller.

Transmission of compressed images is challenging because the communication channels can be noisy and the compressed bitstreams are sensitive to channel errors. Most of the proposed methods in the literature do not guarantee the quality of the received image over noisy channels. We propose an ARQ-based diversity system as a solution, in which the use of the diversity system avoids the problems when one or some channels get congested, and the ARQ scheme guarantees the quality of the received image. A specific ARQ-based diversity system is designed for transmission of images compressed using EZW (embedded zerotree wavelet). Experiments performance results are shown.

We propose an integrated wavelet-based framework for an active contour model (snake) which is used for the motion tracking of deformable objects in a sequence of images. The input image frame is decomposed into a multiresolution representation using a wavelet transform. First, the wavelet transform coefficients are used in a multiresolution motion estimation process to find the initial contour in the frame. The presented multiresolution motion estimation method allows larger movement of the tracked object than the traditional image-based motion estimation. Secondly, the wavelet transform modulus at each scale is considered in the energy function of the active contour model. The application of biological cell tracking using the proposed method is shown as an example.

We develop a multi-channel channel-optimized scheme for embedded zerotree wavelet (EZW) image compression in a noisy transmission environment. A block-based modification for EZW is applied to improve the robustness of EZW, and to produce several coded bitstreams for transmission over multiple channels with different noise conditions. Then the respective channel noise is considered in the rate-distortion analysis, and the resultant rate-distortion functions are used for optimal bit allocation among the coded bitstreams. The case of burst noise is analyzed as an example.

The two-dimensional (2-D) fractional Brownian motion (fBm) model is useful in describing natural scenes and textures. Most fractal estimation algorithms for 2-D isotropic fBm images are simple extensions of the one-dimensional (1-D) fBm estimation method. This method does not perform well when the image size is small (say, 32x32). We propose a new algorithm that estimates the fractal parameter from the decay of the variance of the wavelet coefficients across scales. Our method places no restriction on the wavelets. Also, it provides a robust parameter estimation for small noisy fractal images. For image denoising, a Wiener filter is constructed by our algorithm using the estimated parameters and is then applied to the noisy wavelet coefficients at each scale. We show that the averaged power spectrum of the denoised image is isotropic and is a nearly 1/f process. The performance of our algorithm is shown by numerical simulation for both the fractal parameter and the image estimation. Applications to coastline detection and texture segmentation in a noisy environment are also demonstrated.

We apply the dynamic bit allocation to the block-based EZW algorithm for robust image compression. To optimize the performance of the bit allocation, the effect of the channel noise is concerned. The robustness of our method was evaluated.