The JPEG2000 still image compression standard

The development of standards (emerging and established) by the International Organization for Standardization (ISO), the International Telecommunications Union (ITU), and the International Electrotechnical Commission (IEC) for audio, image, and video, for both transmission and storage, has led to worldwide activity in developing hardware and software systems and products applicable to a number of diverse disciplines [7], [22], [23], [55], [56], [73]. Although the standards implicitly address the basic encoding operations, there is freedom and flexibility in the actual design and development of devices. This is because only the syntax and semantics of the bit stream for decoding are specified by standards, their main objective being the compatibility and interoperability among the systems (hardware/software) manufactured by different companies. There is, thus, much room for innovation and ingenuity. Since the mid 1980s, members from both the ITU and the ISO have been working together to establish a joint international standard for the compression of grayscale and color still images. This effort has been known as JPEG, the Join

Emerging standards for still image compression: A software implementation and simulation study

The software implementation is described of an emerging standard for the lossy compression of continuous tone still images. This software program can be used to compress planetary images and other 2-D instrument data. It provides a high compression image coding capability that preserves image fidelity at compression rates competitive or superior to most known techniques. This software implementation confirms the usefulness of such data compression and allows its performance to be compared with other schemes used in deep space missions and for data based storage

Robust texture features for still-image retrieval

A detailed evaluation of the use of texture features in a query-by-example approach to image retrieval is presented. Three radically different texture feature types motivated by i) statistical, ii) psychological and iii) signal processing points of view are used. The features were evaluated and tuned on retrieval tasks from the Corel collection and then evaluated and tested on the TRECVID 2003 and ImageCLEF 2004 collections. For the latter two the effects of combining texture features with a colour feature were studied. Texture features that perform particularly well are identified, demonstrating that they provide robust performance across a range of datasets

Rotate Intra Block Copy for Still Image Coding

This paper proposes a method called rotate intra block copy, which extends the intra block copy technique by making the block matching process invariant to rotation. HEVC intra prediction plus rotate intra block copy gives an average of 20% reduction in residual energy (i.e. prediction error) compared to HEVC intra prediction plus intra block copy. As the motion vector correlation in rotate intra block copy is different from the intra block copy, a new method of motion vector coding is presented. The impact of angular resolution on residual energy reduction is also evaluated. In a full codec pipeline, this reduction in residual energy translates into a coding gain in BD-rate of 3.4% over HEVC intra prediction plus intra block copy for both screen content and camera-captured gray scale images.Samsung (Firm). Global Research Outreach Progra

License Plate Detection and Recognition from Still Image

Tato práce se zabývá návrhem a vývojem systému pro detekci a rozpoznání registrační značky vozidla. Tento systém je rozdělen na tři části, kterými jsou detekce registrační značky, segmentace znaků a rozpoznání znaků. Pro detekci registrační značky je použita kaskáda klasifikátorů, která dosahuje úspěšnosti až 95,5% a přesnosti 95,9%. Segmentace znaků je provedena pomocí vyhledávání kontur s úspěšností 93,3% a přesností 96,5%. Pro rozpoznání znaků je využita neuronová síť, která dosahuje úspěšnosti 98,4% pro jednotlivé znaky. Celý systém je schopen detekovat a rozpoznat 81,5% registračních značek v pořízené testovací datové sadě.This thesis describes the design and implementation of system for detection and recognition of license plate. This system is divided into three parts which are license plate detection, character segmentation and optical character recognition. License plate detection is done by cascade classifier that achieves hit rate of 95.5% and precision rate of 95.9%. Character segmentation is based on contour finding that achieves hit rate of 93.3% and precision rate of 96.5%. Optical character recognition is done by neural network and achieves hit rate of 98.4% for individual characters. The whole system is able to detect and recognize up to 81.5% of license plates from the test data set.