Research on 3D crack segmentation of CT images of oil rock core

In this paper, we propose a framework for CT image segmentation of oil rock core. According to the characteristics of CT image of oil rock core, the existing level set segmentation algorithm is improved. Firstly, an algorithm of Chan-Vese (C-V) model is carried out to segment rock core from image background. Secondly the gray level of image background region is replaced by the average gray level of rock core, so that image background does not affect the binary segmentation. Next, median filtering processing is carried out. Finally, an algorithm of local binary fitting (LBF) model is executed to obtain the crack region. The proposed algorithm has been applied to oil rock core CT images with promising results.

A Fast Otsu Thresholding Method Based on an Improved 2D Histogram

The regional division of a traditional 2D histogram is difficult to obtain satisfactory image segmentation results. Based on the gray level-gradient 2D histogram, we proposed a fast 2D Otsu method based on integral image. In this method, the average gray level is replaced by the gray level gradient in the neighborhood of pixels, and the edge features of the image are extracted according to the gray level difference between adjacent pixels to improve the segmentation effect. Calculating the integral image from the two-dimensional histogram reduces the computational complexity of searching the optimal threshold, thus reducing the amount of computation. The simulation results demonstrate that the proposed algorithm has better performance in image segmentation, with the increased computational speed and improved real-time capability.

Frequency and average gray-level information for thermal ablation status in ultrasound B-Mode sequences

During thermal ablation in a target tissue the information about temperature is crucial for decision making of successful therapy. An observable temporal and spatial temperature propagation would give a visual feedback of irreversible cell damage of the target tissue. Potential temperature features in ultrasound (US) B-Mode image sequences during radiofrequency (RF) ablation in ex-vivo porcine liver were found and analysed. These features could help to detect the transition between reversible and irreversible damage of the ablated target tissue. Experimental RF ablations of ex-vivo porcine liver were imaged with US B-Mode imaging and image sequences were recorded. Temperature was simultaneously measured within the liver tissue around a bipolar RF needle electrode. In the B-Mode images, regions of interest (ROIs) around the centre of the measurement spots were analysed in post-processing using average gray-level (AVGL) compared against temperature. The pole of maximum energy level in the time-frequency domain of the AVGL changes was investigated in relation to the measured temperatures. Frequency shifts of the pole were observed which could be related to transitions between the states of tissue damage.

Research on Image Seam-Line Removing Based on Illumination Correction

Nowadays, the hard correction is a familiar method for image seam-line removing. But the method needs accurate gray difference around the seam-line which is difficult to achieve occasionally. To overcome such drawbacks, a novel seam-line removing method was proposed in the paper. First, optimal texture matching blocks beside the seam-line are searched, and the average gray level of the two blocks can be obtained. Then, the average gray level of the two blocks is adjusted to estimate the gray level of the same target in different illumination environment. Finally, the illumination is corrected based on the average gray level to remove the seam-line. The theoretical analysis and experiment results show that the proposed method is more effectual then traditional methods.

A Lightweight Dynamic Binarization Method for 2D Barcode Scanning Terminal

It is a difficult task to binarize image under uneven illumination, and this problem is always met in the image recognition system, such as two-dimensional barcode scanning terminal. In this paper, an efficient approach is proposed to binarize image which can tolerant uneven illumination and different light intensity. The method initializes thresholds with local average gray level and adjusts thresholds by calculating light density ratio. Due to characteristic of our approach, it can even obtain a sound result by limiting number of iterations which will seriously reduce computations and space cost. According to experiments, we can find that our method can achieve a good performance and meet the real-time requirement and quality demand for barcode scanning terminal.

Hyperacuity Image Sensors

ABSTRACTThe human visual system perceives much smaller spatial steps in edges between high contrast regions than equivalents fine, periodic features. This characteristic is known as hyperacuity. We have designed, simulated, fabricated and characterized amorphous silicon sensors which provide hyperacuity information. The individual pixels are position sensitive detectors, the outputs of which provide the x and y first moments of the cell illumination pattern as well as the average gray level. In the simplest case the top electrode of a standard p-i-n diode sensor is replaced by four edge strip electrodes. Both quadrilateral cells (having all four lateral electrodes on the same side of the p-i-n diode) and duolateral cells (having x-electrodes on top and y-electrodes on bottom) have been tested. Results of probing the cells with rastered spots show that both types provide usable linearity and sensitivity. The duolateral structure provides greater orthogonality of the x and y information. One μm spatial resolution can be achieved with devices compatible with standard amorphous silicon sensor processing.