Časlav Livada

Beyond the touch: A web camera based virtual keyboard

This paper presents the concept of web camera based virtual keyboard. In order to achieve full functionality of the proposed concept digital image processing methods are being used, such as binarization, morphological operation and filtering. Real time image acquisition is performed by a mid-range quality web camera in order to test the sturdiness of algorithm design. The objective of this research paper is to identify the method of simultaneous fingertip and keyboard character recognition in order to produce a fully functional keyboard for user input.

Compression parameters tuning for automatic image optimization in web applications

In this paper an automatic image optimization workflow for web applications is proposed. The workflow consists of several parts: a JPEG encoder, a perceptual visual quality metric (PVQM) and a system for automatic iterative compression of the images. The system for automatic compression iteratively compresses the image and tries to determine the highest compression rate for each image, without compromising the perceptual quality of the image. To evaluate the proposed PVQM parameter used for stopping the iterative compression, a study is performed where 155 users rated random selection from 559 versions of differently compressed images from a public dataset. All images are high quality images in high resolution, which makes them suitable for use in web applications. For JPEG encoder we evaluate very popular open source software package: mozjpeg from Mozilla. The results show which values of PVQM metric should be used to obtain a desired trade-off between compression ratio and subjective loss of quality.

Comparison of different PDE-based image compression methods with respect to the choice of PDE

In recent times there is an increasing number of publications that explore potential of partial differential equations (PDEs) as image compression methods. PDEs are frequently used for interpolation problems even when data is sparse. In PDE-based image compression only a part of data is stored by various sparsification methods while in decompression stage missing data is restored. Goal of the presented paper is to explore the potential of PDEs for image compression and importance of selecting an appropriate PDE for compression and decompression. PDE-based interpolation and image compression methods are described and a number of different PDEs are evaluated for compression.

Image compression with B-tree coding algorithm enhanced by data modelling with Burrows-Wheeler transformation

The paper shows that the partial differential based compression framework, Edge Enhancing Diffusion Compression (EEDC) on high compression ratios can come close to or even be better than present compression standard -JPEG2000 thus presenting a novel method for image compression. In this paper EEDC will be enhanced by changing its data coding, i.e. Huffman coding will be changed with an entropy coder accompanied with Burrows-Wheeler transformation and context mixing. Images, graphs and tables show image compression results. The purpose of this article is to examine the effectiveness of the PDEs in image compression and to evaluate it by comparing to cosine and wavelet transform based compression methods.

Cardiac CT image enhancement for 3D heart registration and visualization

Cardiac CT imaging has been established as one of the most valuable tools in diagnosis and treatment of cardio vascular diseases. Modern CT imaging devices provide a significant amount of data with high precision. However, resulting CT images can often suffer from significant quality degradations, especially in the preferable case of low level of radiation. Such degradations can complicate the registration and visualization processes, thus making it harder for medical doctors to analyze the acquired data. The goal of this paper is to propose a method for the enhancement of input CT data based on Multiscale Wavelet Decomposition and Spatial Pixel Profiling in 2D slices. Proposed methods are used as preprocessing steps on input CT data, preparing the data for segmentation and registration using Active Contour Models segmentation method. This paper displays the benefits of such approach for the purpose of 3D reconstruction.

Visual repercussions of the noise induced errors in the communication channel on compressed images

This research analyzes the susceptibility to errors in the communication channel of the two standards in image compression - JPEG and JPEG 2000. Errors are introduced to the bit stream via channel noise, i.e. Gauss, Poisson, uniform noise and their influence to image quality is measured by objective and subjective image quality assessment methods. A novel compression method based on partial differential equations is introduced as a direct contender to two before mentioned standards.

Image segmentation using active contour models and partial differential equations

This article displays benefits of image segmentation for purpose of 3D reconstruction. Medical images and in this case CT slices are being reconstructed in 3D space for better medical investigation. It is relatively hard to use raw images for 3D reconstruction, so certain areas are being singled out using active contour models. Partial Differential Equations (PDEs), as non-linear diffusion, are used for image denoising because CT images have large gradiental areas that need to be evened out.