Image segmentation with scalable spatial information

A general approach is proposed for the design of image segmentation algorithms utilizing spatial information which is the combined properties of a collection of neighborhood pixels. With different types of properties and different number of neighborhood pixels being utilized, segmentation algorithms with different speed and accuracy performance can be designed. Six algorithms have been implemented with their performance investigated and compared.published_or_final_versio

Maximum a posteriori spatial probability segmen

An image segmentation algorithm that performs pixel-by-pixel segmentation on an image with consideration of the spatial information is described. The spatial information is the joint grey level values of the pixel to be segmented and its neighbouring pixels. The conditional probability that a pixel belongs to a particular class under the condition that the spatial information has been observed is defined to be the a posteriori spatial probability. A maximum a posteriori spatial probability (MASP) segmentation algorithm is proposed to segment an image such that each pixel is segmented into a particular class when the a posteriori spatial probability is a maximum. The proposed segmentation algorithm is implemented in an iterative form. During the iteration, a series of intermediate segmented images are produced among which the one that possesses the maximum amount of information in its spatial structure is chosen as the optimum segmented image. Results from segmenting synthetic and practical images demonstrate that the MASP algorithm is capable of achieving better results when compared with other global thresholding methods.published_or_final_versio

Nondestructive Testing Potential of a Magnetoacoustic Storage Correlator (MASC)

A simple magnetoacoustic storage correlator (MASC) was tested as a pulse compressor in an ultrasonic nondestructive testing application. The pulse compression ratio reached was 30. Higher compression ratios are readily available through choice of different device lengths and device operating regime. The system is flexible; it is not limited to any particular type of large time-bandwidth signal. The correlator reference signal is easily programmable and erasable, and can be changed at any time. This system offers real-time correlation signal processing at a repetition rate that is only limited by the temporal length of the large time-bandwidth signal

An iterative image segmentation algorithm utilizing spatial information

An iterative image segmentation algorithm that segments an image on a pixel-by-pixel basis is described. The observation information to be utilized is the joint gray level values of the pixel to be segmented and those of its neighborhood pixels. The iterative process is initialized by thresholding the image with Otsu's (1979) method. Each pixel is segmented into a class when the a posteriori probability, conditioned on the observation information, that it belongs to this class is a maximum. The newly segmented image is employed to re-estimate the a posteriori probabilities and the segmentation process is repeated until there is no further pixel classification change in a particular run. Among those segmented images generated in the iterative process, the best segmented image is chosen, according to a maximum entropy criterion. Simulation studies demonstrate that the proposed algorithm can achieve very significant improvement in segmentation performance as compared to the more popular thresholds approach. Furthermore, the performance is neither sensitive to the initial threshold value nor the form of the probability density function of the image. Segmentation of practical images also demonstrates that the proposed algorithm is capable of good segmentation results for real-life images.published_or_final_versio

Ultrasonic Detection using Wideband Discrete Wavelet Transform

This paper describes the design of a wideband spatial processor for the detection of a straight-line object by an ultrasonic pulse-echo detection system. An ultrasonic pulse is transmitted from the transducer and the two wavelets diffracted from the two end points of the straight-line object are received by three spatially separated receivers. Three stages of signal processing are carried out. At the first stage, the mother wavelet operator generates three sets of two-dimensional wavelet coefficients. At the second stage, cross wavelet transforms are performed on wavelet coefficients obtained in the first stage. At the third stage, cross wavelet transforms are performed on cross wavelet coefficients obtained in the second stage. As a result of this three-stage operation, a high-resolution image of the environment is generated and the range and bearing of the two end points of the straight-line object are obtained. A simulation program is developed to investigate the processing algorithm in an ultrasonic detection environment.published_or_final_versio

Segmentation of pathology microscopic images

The light microscopic analysis of the number and shape of cells in pathology is important for the diagnosis and assessment of clinical behavior of disease conditions. The fundamental step of this work is to separate the cells from the background. To segment objects from such uneven background images, a fixed threshold is not suitable. The authors have proposed a new adaptive thresholding method using variational theory. In this paper, this method is introduced to segment pathological images under the light microscope. The comparison of the segmentation results of the authors' method and Otsu's (1979) thresholding method shows the advantage of the authors' method.published_or_final_versio

Adaptive thresholding by variational method

When using thresholding method to segment an image, a fixed threshold is not suitable if the background is uneven. Here, we propose a new adaptive thresholding method using variational theory. The method requires only one parameter to be selected and the adaptive threshold surface can be found automatically from the original image.published_or_final_versio

A fast deformable region model for brain tumor boundary extraction

We present a modified deformable region model for extraction of a brain tumor boundary in 2D MR images. The deformable region model tolerates a rough initial plan when compared with the active contour model. However, it is time consuming to compute and compare the gray level distribution of the object and all its boundary points. Using a point sampling technique, the number of boundary point processed is greatly reduced. Performance of our modified deformable region model is evaluated on a MR image. The modified model is fast while similar results are obtained.published_or_final_versio

Visual evoked potential estimation by eigendecomposition

In this paper an eigendecomposition method is presented to estimate evoked potentials (EP). Taking into account of the characteristic of evoked potentials, the method uses two observations both of which contain desired EP signal and undesired EEG signal. If the desired and undesired signal are uncorrelated (i.e. they are orthgonal) and the signal-to-noise-ratios (SNR) of each observations are different, we can use the eigendecomposition method to separate EP signal from EEG. Visual evoked potentials (VEP) of humans have been estimated and good results obtained by this method.published_or_final_versio

A Fast Signal-Dependent Time-Frequency Representation

In last few years, in order to overcome same limitations of the short time Fourier transform (STFT), while avoiding the cross-terms that make the Wigner distribution difficult to interpret, some signal-dependent time-frequency representations (SDTFR) have been proposed. In this paper, the authors introduce a computationally efficient signal-dependent time-frequency method which is suitable for on-line analysis. This SDTFR uses a Gaussian window (GW) similar to STFT, but varies the parameter σ of the GW with time to achieve high signal concentration and high resolution in time. The parameter σ can be automatically calculated by the slope of instantaneous frequency (IF) and instantaneous bandwidth (IB) at that time.published_or_final_versio