Jianhong Zhou

Structural damage detection based on wavelet transform in strain energy signal processing

Structural damage detection is of great significance for engineering applications. Most damage detection methods are vibration-based methods. In this paper, we propose a method for damage detection of structures under static loads. The wavelet transform technique is introduced in the spatially distributed strain energy signal processing. We can use the singularity of wavelet coefficients to determine the damaged location. Numerical examples under four cases of damages are provided to illustrate the applicability of the proposed method. We use the element stiffness reduction to simulate the damage. The results of the damaged cases have indicated that the different damage locations in a structure can be precisely determined using the proposed method. The damage detection method proposed in this paper can be introduced for engineering applications.

Multi-focus image fusion algorithm based on non-subsampled shearlet transform and focus measure

novel multi-focus image fusion algorithm is proposed in the Sheartlet domain. The core idea of this paper is to utilize the focus measure to detect the focused region from the multi-focus images. The proposed algorithm can be divided into three procedures: image decomposition, sub-bands coefficients selection and image reconstruction. At first, the multi-focus images are decomposed by non-subsampled Sheartlet transform (NSST), and the low frequency sub-bands and high frequency sub-bands can be obtained. For the low frequency sub-bands, saliency detection and improved sum-modified-Laplacian are combined to detect the focused regions. A modified edge measure algorithm is utilized to guide the coefficients combination for high frequency sub-bands at different levels. Moreover, in order to avoid the erroneous results introduced by the above procedures, mathematical morphology technique is used to revise the decision maps of the low frequency sub-bands and high frequency sub-bands. The final fused image can be obtained by taken the inverse NSST. The performance of the proposed method is tested on series of multi-focus images extensively. Experimental results indicate that the proposed method outperformed some state-of-the-art fusion methods, in terms of both subjective observation and objective evaluations.

Implementation and performance evaluation open-source controller for precision control of gripper

This paper proposes integrating gripper embedded operating system, which consist of external interface structure for sophisticated gripper control. This system has multiple functions that control the gripping module and measure the pose of the gripper body with respect to contact environment. A controller based on open source only for the gripper is developed and an external communication interface between robot controller and gripper controller is designed. An experimental environment for the fixed-cycle test consists of integrating magic gripper software system and hardware on commercial business. As a result, a deviation is measured approximately 2% and the system were verified for gripper control.

Feature extraction of the wafer probe marks in IC packaging

This paper presents an image processing approach to extract six features of the probe mark on semiconductor wafer pads. The electrical characteristics of the chip pad must be tested using a probing needle before wire-bonding to the wafer. However, this test leaves probe marks on the pad. A large probe mark area results in poor adhesion forces at the bond ball of the pad, thus leading to undesirable products. In this paper, we present a method to extract six features of the wafer probe marks in IC packaging for further digital image processing.

A novel ECG data compression method based on adaptive Fourier decomposition

This paper presents a novel electrocardiogram (ECG) compression method based on adaptive Fourier decomposition (AFD). AFD is a newly developed signal decomposition approach, which can decompose a signal with fast convergence, and hence reconstruct ECG signals with high fidelity. Unlike most of the high performance algorithms, our method does not make use of any preprocessing operation before compression. Huffman coding is employed for further compression. Validated with 48 ECG recordings of MIT-BIH arrhythmia database, the proposed method achieves the compression ratio (CR) of 35.53 and the percentage root mean square difference (PRD) of 1.47% on average with N = 8 decomposition times and a robust PRD-CR relationship. The results demonstrate that the proposed method has a good performance compared with the state-of-the-art ECG compressors.

Differential effects of gender on entropy perception

The purpose of this research is to examine differences in perception of entropy (color intensity) between male and female computer users. The objectives include identifying gender-based differences in entropy intention and exploring the potential effects of these differences (if any) on user interface design. The research is an effort to contribute to an emerging field of interest in gender as it relates to science, engineering and technology (SET), particularly user interface design. Currently, there is limited evidence on the role of gender in user interface design and in use of technology generally, with most efforts at gender-differentiated or customized design based on stereotypes and assumptions about female use of technology or the assumption of a default position based on male preferences. Image entropy was selected as a potential characteristic where gender could be a factor in perception because of known differences in color perception acuity between male and female individuals, even where there is no known color perception abnormality (which is more common with males). Although the literature review suggested that training could offset differences in color perception and identification, tests in untrained subject groups routinely show that females are more able to identify, match, and differentiate colors, and that there is a stronger emotional and psychosocial association of color for females. Since image entropy is associated with information content and image salience, the ability to identify areas of high entropy could make a difference in user perception and technological capabilities.

Parking-lines detection based on an improved Hough transform

The parking-lines recognition is a prerequisite for the vehicle automatic parking system. This paper adopts Otsu threshold segmentation method, Sobel operator and improved Hough transform to realize the detection of parking lines. The experimental results show that the algorithm can effectively and accurately identify the parking lines.

Binary image filtering for object detection based on Haar feature density map

The most concerned problem is to detect the interesting objects in image sequence captured from the same scene. Image difference is a commonly used method in detecting the interesting object, however, massive noise exists in the binarized difference image, so how to remove the noise is a hot issue. Aiming at the removing the noise in binary difference image, we propose a novel filtering algorithm based on Haar feature density map. Firstly, calculate the Haar feature density distribution map of binary image. Secondly, the density distribution map of Haar feature is binarized to remove noise. Finally, the interesting objects can be easily detected. Experiments show that the Haar feature density map achieves a better filtering effect than the conventional filtering algorithms for binary image (such as median filtering, morphological operation and so on).

A formation control strategy with coupling weights for the multi-robot system

The distributed formation problem of the multi-robot system with general linear dynamic characteristics and directed communication topology is discussed. In order to avoid that the multi-robot system can not maintain the desired formation in the complex communication environment, the distributed cooperative algorithm with coupling weights based on zipf distribution is designed. The asymptotic stability condition for the formation of the multi-robot system is given, and the theory of the graph and the Lyapunov theory are used to prove that the formation can converge to the desired geometry formation and the desired motion rules of the virtual leader under this condition. Nontrivial simulations are performed to validate the effectiveness of the distributed cooperative algorithm with coupling weights.

Illumination robust face recognition using spatial adaptive shadow compensation based on face intensity prior

Robust face recognition under illumination variations is an important and challenging task in a face recognition system, particularly for face recognition in the wild. In this paper, a face image preprocessing approach, called spatial adaptive shadow compensation (SASC), is proposed to eliminate shadows in the face image due to different lighting directions. First, spatial adaptive histogram equalization (SAHE), which uses face intensity prior model, is proposed to enhance the contrast of each local face region without generating visible noises in smooth face areas. Adaptive shadow compensation (ASC), which performs shadow compensation in each local image block, is then used to produce a wellcompensated face image appropriate for face feature extraction and recognition. Finally, null-space linear discriminant analysis (NLDA) is employed to extract discriminant features from SASC compensated images. Experiments performed on the Yale B, Yale B extended, and CMU PIE face databases have shown that the proposed SASC always yields the best face recognition accuracy. That is, SASC is more robust to face recognition under illumination variations than other shadow compensation approaches.