Automatic Change Detection System Research Articles

An onboard automatic change detection system for disaster monitoring

This paper presents a new approach to disaster monitoring using an automatic change detection system onboard small satellites that features image tiling and fuzzy inference. Unlike other onboard change detection systems for satellites, the proposed system performs change detection on an image tile level rather than on a pixel-by-pixel basis. This image tiling approach allows for more robust change detection performance in the presence of misregistration errors. An important block in the automatic change detection system is the fuzzy inference engine, which generates control signals that trigger different onboard tasks such as image compression, issuing of warning alerts, transmission and rescheduling. The proposed scheme uses not only spectral information as the input data but also cloud cover information to improve the change detection results. Experimental results on accuracy of change detection and flood detection using satellite images are presented.

An intelligent decision-making system for flood monitoring from space

This paper presents the results of a feasibility study on intelligent image processing for flood monitoring on board satellites. The ability to detect temporal changes in images is one of the most important functions in intelligent image processing systems for hazard and disaster monitoring applications. An automatic change detection system is proposed, the purpose of which is to monitor particular areas on earth for flooding events and give warnings to the authorities accordingly. A novel solution to flood detection based on the combined use of optical multispectral imagery and global positioning system reflectometry data is introduced. A fuzzy inference engine is used in the decision-making process, which generates control signals to other subsystems on board the satellite.

Visual mismatch negativity highlights abnormal pre-attentive visual processing in mild cognitive impairment and Alzheimer's disease

Alzheimer's disease (AD) and mild cognitive impairment (MCI) are traditionally characterised in relation to abnormalities in higher-level brain function, particularly memory. However, in the study presented here we report significant abnormality in pre-attentive visual processing in both MCI and AD compared to healthy ageing. The functional integrity of the automatic change detection system was determined by measuring the visual mismatch negativity (vMMN) component of the N2 visual event-related potential (ERP) in 8 individuals with amnestic MCI, 10 individuals with AD and 10 healthy older adult controls. Compared to healthy ageing, both the MCI and AD groups displayed a significant abnormally increased vMMN over the 140–250ms measurement epoch although such effects were not apparent over the later 250–400ms epoch. These novel findings support the view that deficits in brain function in both AD and MCI are not exclusively high-level and indeed that abnormal output from ‘low level’ or pre-attentive processes (as evinced by the abnormal vMMN) is likely to contribute to the high-level processing deficits so characteristic of these clinical disorders.

The vanishing point of the mismatch negativity at sleep onset

Objective: To determine when the mismatch negativity (MMN) disappears at sleep onset, event-related potentials (ERPs) were recorded continuously from wakefulness to sleep. Methods: Ten healthy young students were told to fall asleep ignoring the tones presented through a loudspeaker above their head. Standard (1000 Hz, P=0.90), high deviant (1200 Hz, P=0.05), and low deviant (1050 Hz, P=0.05) tones were presented in a quasirandom order with a fixed stimulus onset asynchrony of 500 ms. ERP waveforms were obtained separately for 5 successive stages characterized by typical electroencephalographic (EEG) patterns of the sleep onset period. The EEG staging was made manually with very short (5 s) scoring epochs. Results: The MMN appeared in wakefulness and in the early phase of stage 1 sleep (EEG stage II) but disappeared when low-voltage theta waves emerged after alpha flattening (EEG stage III). Instead, P240 and N360 developed particularly for high deviant tones. Conclusions: Concurrently with the disappearance of alpha waves, the automatic change detection system in wakefulness seems to stop operating and a different sleep-specific system becomes dominant.

地図データ更新における変化部自動抽出の試み

Necessity of an automatic change detection method was emphasized for efficient map revision. The significance and problems of utilizing existing old maps for a change detection system were discussed. A couple of problems in applying basic image understanding techniques to change detection were reviewed, and an attempt was made to solve them with a prototype system developed for use with satellite images and map data.The attempt clarified that every automatic change detection system outputs some errors in its results, and that such systems must have some efficient error inspection functions incorporated well with human inspection capability in order to be practically used. An example of such inspection systems was also presented.