Structuring element

About: Structuring element is a research topic. Over the lifetime, 997 publications have been published within this topic receiving 26839 citations.

Location Time of Power Quality Disturbances and Noise Using Morphology Gradient and Skeletonization in 3D

Abstract: In power system, there are some disturbances such as, voltage dip, momentary interruption, voltage swell, or oscillatory transients that may result in mal-function or failure in operation of some devices. Knowing the location where the disturbances occur in the system is an essential part in selecting the appropriate method on improving power quality issues in order to get effective and efficient results. One of methods in locating power quality disturbances is using Mathematical Morphology (MM). In this paper, signals with disturbances were filtered using morphology gradient. Top-hat transform is applied for the filtered signal using flat structuring element. The simulation results show that the location of disturbances can be detected accurately. Skeletonization is used to identify the location time of the noises in the system. By plotting the results in 3D, it makes easier to identify the location of disturbances with or without noises from their different color and shape as pattern recognition.

A smoothing method of lofargram using morphological opening filter(part 2): Utilization of structuring element on time-frequency space.

Abstract: To suppress impulse noise on lofargram, we have proposed a smoothing method using morphological opening filter on time-axis. The computer simulation results have shown effective improvements of processing gain and time-resolution as compared with that of averaging procedure. However, same frequency components will not be maintained in target signal at any time. In this case, morphological opening filter on time-axis removes the parts of the target signal in which the frequency components vary with time. It is a disadvantage of this method.In this paper, morphological opening filter using structuring element on time-frequency space is tried to smooth the lofargram. Two types of the sound data are in use to verify this method. The firsts are simulated on computer. The second data are measured in practice. The simulation results in this paper show effective improvements of processing gain. Then, the lofargram outputs of both data can visualize the target signals, the frequency components of which vary with time. We confirm that the smoothing method using the structuring element on time-frequency space outweighs the disadvantage of that on time-axis.

Medical Ultrasound Image Denoising Based on Adaptive Morphological Despeckling Filter

Abstract: In view of speckle noise in medical ultrasound image, a denosing method based on adaptive morphological filter was proposed. Firstly, a set of structuring factors was constructed to detect different sudden changes of pixel values in images. Then a corresponding structuring element for morphological filtering was established for each structuring factor. Finally, the most possible structures of sudden changes in each pixel’s neighborhood were detected by using the set of structuring factors and a morphological filtering was performed to the pixel with the corresponding structuring element. The comparison experiment was carried out on simulated and real ultrasound images by using the proposed method, the speckle reducing anisotropic diffusion and different scale morphological filters, respectively. It is shown that the proposed method averagely improves the Signal-to-noise Ratio (SNR), Contrast-to-noise Ratio (CNR) and Figure of Merit (FOM) of ultrasound images by 15%, 37% and 69%. Therefore, the adaptive morphological despeckling filter may be an effective method to suppress speckle in ultrasound images.

Morphological processing of videostream frames binary masks

Abstract: One of the primary tasks of videoframes processing of digital videostreams is to quantify the geometric structure of moving objects, in order to extract information from videostreams frames. In this paper we purpose a recursive algorithms that are based on morphological conditional dilation and conditional erosion operations. Practical implementation of purposed algorithms on real-time video sequences shows, that computational complexity of purposed algorithms is equal to m+1, where m — number of pixels in kernel.

VLSI chip architecture design for 2-D gray-level morphological operations

Abstract: The basic operations of mathematical morphology are quite useful for a broad area of image processing and analysis tasks. All morphological operations can be built from erosions and dilations. In this paper we develop a single chip VLSI architecture of an erosion/dilation algorithm for real-time image processing. The new architecture allows sequential inputs and performs parallel processing with 100 percent efficiency. The erosions (mm of differences) and dilations (max of additions) operate on 2-D gray-level image signals and use a 5 x 5-pixel gray-level structuring element. Two chips can be cascaded for a 7 x 7 structuring element. The overall chip design also provides the user with sufficient flexibility to optionally offset the output images by adding a constant level and/or scale their dynamic range. 1.