Integrating Local Binary Patterns into Normalized Moment of Inertia for Updating Tracking Templates

Song, H; Xiao, Botao; Hu, Qinzhen; Ren, Peng

doi:10.1049/cje.2016.07.016

Cited by 6 publications

(3 citation statements)

References 7 publications

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“…Ref. [17] presents an efficient visual tracking framework which is robust to rotation, scale variation and occlusion. Some steps in their technique like locally pyramid searching are not necessary for our task, but in other tasks where the scenario is more dynamic, this may be the solution.…”

Section: Rat Foreground Extractionmentioning

confidence: 99%

A Posture Recognition System for Rat Cyborg Automated Navigation

Zhang

Yang

et al. 2018

Chin. j. electron.

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Section: Rat Foreground Extractionmentioning

confidence: 99%

A Posture Recognition System for Rat Cyborg Automated Navigation

Zhang

Yang

et al. 2018

Chin. j. electron.

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“…Researchers have proposed many different methods of texture feature extraction to describe the texture information of images, including grey‐level co‐occurrence matrix (GLCM) [2], Markov random field (MRF) model [3], discrete wavelet transform (DWT) [4], local binary pattern (LBP) algorithm [5]and so on. As a single texture feature cannot fully represent the texture information, the feature fusion method is proposed.…”

Section: Introductionmentioning

confidence: 99%

Multi‐features fusion classification method for texture image

Jing

Zhang

Jiang

2019

J. eng.

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“…Moreover, some techniques are involved in our approach to cope with the situations just mentioned. In order to track a target under variant illumination or a moved situation, a technique to update the template could be helpful [14][15][16][17]. Considering the localization capability under variant illumination and dusky environments, edge-based geometric matching and pyramidal gradient matching techniques are embedded in our approach instead of template updating to localize the wanted regions of interest (ROI) of the A-meter (refer to the main stages of instrument meter region detection, angle detection of pointer as well as angle detection of selector arrow in the flowchart of Figure 2).…”

Section: Introductionmentioning

confidence: 99%

Computer Vision-Based Approach for Reading Analog Multimeter

Chen

Wang

2018

Applied Sciences

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Multimeters are useful instruments for measuring electronic parameters. Even though the digital multimeter is commonly used in our daily life under the considerations of precision and cost, the analog multimeter is still preferable in many applications due to its easy use to monitor promptly varying values. However, the reading of analog multimeters (or A-meter) usually relies on human eyes with two obvious drawbacks of inefficiency and easy fatigue, while visual inspection onto an A-meter is needed for a long period of time. From the viewpoint of optical sensor application, computer vision, like human eyes, can also be used to sense stimuli from the real world. Therefore, in this paper, an approach of reading an A-meter based on a computer vision technique is proposed. Reading an A-meter relies on information from the arrow on the function selector and the pointer on the instrument meter; the presented method is thus mainly composed of horizontal alignment of the A-meter, detection of the instrument meter region, angle detection of the selector arrow, and angle detection of the pointer. In addition, the schemes of edge-based geometric matching (EGM) and pyramidal gradient matching (PGM) are adopted to detect the regions of interest. The mapping relationship between the function selector and the selector arrow as well as that between the instrument meter and the pointer are built and formulated to finally read the A-meter. The often used scenarios for reading AC voltage, DC voltage, and DC current as well as resistance are used for experiments and evaluations. The experimental results show that the accuracy of detecting the function selected is 100%, the mean accuracy of reading a value from the A-meter is 95% or above, except for some cases of reading resistance that are affected by the so-called little-change-large-multiplier effect. The proposed method can perform very well as long as the mean intensity is ≥ 7.5. Based on a suitable modification of the proposed method, an application of monitoring a storage level meter and pressure meter installed on a 15 m 3 liquid nitrogen (LN2) tank is demonstrated. Our experiments and demonstrations confirm the feasibility of the proposed approach.

show abstract

Integrating Local Binary Patterns into Normalized Moment of Inertia for Updating Tracking Templates

Cited by 6 publications

References 7 publications

A Posture Recognition System for Rat Cyborg Automated Navigation

A Posture Recognition System for Rat Cyborg Automated Navigation

Multi‐features fusion classification method for texture image

Computer Vision-Based Approach for Reading Analog Multimeter

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