Iris image quality evaluation plays a very important part in iris computer recognition. An iris image quality evaluation method was introduced into this study to distinguish good image from bad image caused by pupil distortion, blurred boundary, two circles appearing not concentric, and severe occlusion by eyelids and eyelashes. The tests based on this method gave good results.
Humans ; Image Enhancement ; methods ; Image Interpretation, Computer-Assisted ; Iris ; anatomy & histology ; Pattern Recognition, Automated ; methods ; Photogrammetry ; methods ; standards

23 subjects' 8-lead (Fp1, Fp2, Cp3, Cp4, T7, T8, P7, P8) electroencephalogram (EEG) was recorded when they were doing mental arithmetic at four different levels. We calculated the information transmission time series in human cerebral cortex basing on EEG, and the Lempel-Ziv complexity and C1C2 complexity of these time series. When 20 subjects were doing the most difficult mental arithmetic, the information transmission series between lead at left-brain (Cp3, T7, P7) and other leads was of more complexity than others; a light "cross" could be seen after the information transmission matrix was converted to image; when complexity was calculated, the difference was more significant by use of C1 complexity than by other complexity measures.
Cerebral Cortex ; physiology ; Electroencephalography ; Humans ; Intelligence Tests ; Signal Processing, Computer-Assisted ; Synaptic Transmission ; physiology

To extract texture features from medical images, the approaches for multi-scale complexity and multi-scale fractal dimension were proposed in this paper. The extracted texture features were used in the medical image retrieval experiments. The complexity measurements used include permutation entropy and 2D-C0 complexity. The former is used to analyze one dimensional signal, and the latter is used to analyze two dimensional one. Comparison experiments were carried out between our approaches and others' approaches in some literatures. Preliminary experimental results show that our approaches can effectively describe the texture information of medical images. Furthermore, the image retrieval results are encouraging.
Automation ; Diagnostic Imaging ; Humans ; Information Storage and Retrieval ; methods ; Nonlinear Dynamics

In present, the most basically used parameters for speaker identification are linear predictive coding (LPC) parameter, Mel frequency cepstrum coefficient(MFCC), etc. First in this paper only MFCC was used as the parameter and then Lempel-Ziv Complexity was combined with MFCC as parameters. The text-dependent recognition rate of 50 speakers increased from 42% to 80% and the text-independent recognition rate of 50 speakers increased from 60% to 72%. This test shows that Lempel-Ziv complexity, as a new parameter, can be applied to speaker identification.
Algorithms ; Artificial Intelligence ; Female ; Humans ; Male ; Nonlinear Dynamics ; Pattern Recognition, Automated ; methods ; Signal Processing, Computer-Assisted ; Voice