Michael Ansorge

Adaptive color image compression based on visual attention

This paper reports an adaptive still color image compression method which produces automatically selected ROI with a higher reconstruction quality with respect to the rest of the input image. The ROI are generated on-the fly with a purely data-driven technique based on visual attention. Inspired from biological vision, the multicue visual attention algorithm detects the most visually salient regions of an image. Thus, when operating in systems with low bit rate constraints, the adaptive coding scheme favors the allocation of a higher number of bits to those image regions that are more conspicuous to the human visual system. The compressed image files produced by this adaptive method are fully compatible with the JPEG standard, which favors their widespread utilization.

GSM speech coding and speaker recognition

This paper investigates the influence of GSM speech coding on text independent speaker recognition performance. The three existing GSM speech coder standards were considered. The whole TIMIT database was passed through these coders, obtaining three transcoded databases. In a first experiment, it was found that the use of GSM coding degrades significantly the identification and verification performance (performance in correspondence with the perceptual speech quality of each coder). In a second experiment, the features for the speaker recognition system were calculated directly from the information available in the encoded bit stream. It was found that a low LPC order in GSM coding is responsible for most performance degradations. By extracting the features directly from the encoded bit-stream, we also managed to obtain a speaker recognition system equivalent in performance to the original one which decodes and reanalyzes speech before performing recognition.

Adaptive block-size transform coding for image compression

In this paper we report the results of an adaptive block-size transform coding scheme that is based on the sequential JPEG algorithm. This minimum information-overhead method implies a transform coding technique with two different block sizes: N/spl times/N and 2N/spl times/2N pixels. The input image is divided into blocks of 2N/spl times/2N pixels and each of these blocks is classified according to its image activity. Depending on this classification, either four N-point or a single 2N-point 2-D DCT is applied on the block. The purpose of the algorithm is to take advantage of large uniform regions that can be coded as a single large unit instead of four small units-as it is made by a fixed block-size scheme. For the same reconstruction quality, the results of the adaptive algorithm show a significant improvement of the compression ratio with respect to the non-adaptive scheme.

VLSI systems for image compression: a power-consumption/image-resolution trade-off approach

Low power consumption is a requirement for any battery powered portable equipment. When designing ASICs for image and video compression, emphasis has been placed mainly on building circuits that are fast enough to satisfy the high data throughput associated with image and video processing. The imminent development of portable systems featuring full multimedia applications, adds the low-power constraint to the design of VLSI circuits for this kind of application. Several techniques such as lowering the supply voltage, architectural parallelization, pipelining etc., have been proposed in the literature to achieve low-power consumption. In this paper we report a VLSI circuit featuring a power management user-controllable technique that trades image quality for power consumption in a transform-based algorithm.

An 8-bit low-power ADC array for CMOS image sensors

The paper presents an original analog-to-digital converter (ADC) array meeting the constraining requirements in resolution, speed, size, and low power consumption of high-performance low-cost video cameras. The converter array is based on ADC cells relying on a cyclic redundant signed digit (RSD) algorithm supporting comparators with extended tolerance. A prototype ADC array composed of 32 converters was integrated in a 1 /spl mu/m CMOS process and tested. It is featuring an 8 bit resolution for an active area of 2.1 mm/sup 2/, and a power consumption of 4 mW at a sampling rate of 4.2 MS/s, with a voltage supply of 2.6 V. Typical DNL and INL values of -0.5/+0.2 and /spl plusmn/0.4 LSB, respectively, were measured for each ADC cell. Moreover, an overall SNR of 45 dB can be achieved with a digital off-chip offset compensation.

Effective static response compensation suitable for low-power ASIC implementation with an application to pressure sensors

This paper presents an efficient all-digital compensation technique for sensors measuring static or slowly-varying quantities such as pressure. The proposed solution compensates the temperature dependencies and further non-linearities affecting the accuracy and measurement range of the sensors. In addition, for the considered pressure sensors, the trimming that is usually performed in factory can be replaced by a measure of the sensor characteristics to be used for the digital sensor compensation. The whole design procedure, starting from the description of the pressure sensors down to the low-power ASIC implementation of the processor architecture is discussed in detail.

Automatic classification of wideband acoustic signals

Until now, very few contributions were published in the field of wideband acoustic signal recognition, especially for handling impulsive noise signals such as glass breaking, detonations, or door slams, as encountered in security applications, where the signals are highly nonstationary and composed of higher frequency components. This paper shows how the audio alarm recognition problem can efficiently be tackled using either pattern recognition methods relying on Bayes classifiers, or on artificial neural networks (ANN). After extraction of filterbank coefficients in the acoustic analysis module, typical feature vectors are achieved from the concatenation of k consecutive signal frames, in order to exploit dynamic temporal information. The redundancy induced by this dynamic modeling requires a reduction of the feature space dimension, performed with a conventional principal component analysis. The performance of both systems is evaluated experimentally (7000 tests) for the classification of three types of...

Smart low-power CMOS cameras for 3G mobile communicators

The paper presents the concept of a smart multifunctional low-power camera for 3G mobile communicators and Personal Digital Assistants. The device is composed of an ultra low-power image sensor featuring a large intra-scene dynamic range and a high sensitivity, so as to ensure proper image acquisition under possibly severe illumination conditions, as encountered in mobile. Further embedded functionalities encompass low-power still image compression, and low-power face authentication for secured access control.

Countering illumination variations in a video surveillance environment

In the field of video technology for surveillance applications it is often necessary to cope with the phenomenon of illumination variations. In fact, if not compensated, such variations can falsely trigger the change detection module that detects intrusions in video surveillance systems, thus affecting their reliability. Many studies have been made to solve the change detection problem under varying illumination conditions. Most of the published methods, however, rely only on the luminance information. The algorithm proposed in this paper exploits independently the information of each band of the RGB color space of the video sequences, thus producing a change detection algorithm that is more robust to illumination variations. These illumination variations are globally modeled by the so- called Von Kries model (also known as diagonal scaling model). This model is generally used to solve the color constancy problems, where conformance to a reference image illumination has to be guaranteed, like in color image retrieval applications. The use of this model is motivated by its low computational cost and by the interest of studying the relationship between color constancy and change detection. Based on practical experiments which confirm the interest in this method, new and more robust change detection algorithms are expected to be designed. In addition, the paper proposes the use of an iterative scheme whose aim is to improve the results obtained in the change detection module, and which is independent of this module, i.e., it can be used with other change detection schemes. It will be shown that the iteration can improve the quality of the final change mask, thus permitting to obtain a more effective change detection scheme.

On the automated symbolic design of wave digital filters

An experimental software tool has been developed for the automated symbolic design of state-space wave digital filters (WDFs) using exact behavior-preserving transformations. This software tool supports in particular the design of essentially equivalent state-space WDFs based on analog LC ladder reference filters. However, it can also be used to generate other kinds of state-space filters. The symbolic derivation of the state-space WDFs is advantageous, since it simplifies later computation-intensive optimizations (e.g., filter coefficient optimization) and limits numerical error-propagation effects.<<ETX>>