Image rotation-elimination based on a retina-like sensor

Cao, Fengmei; Lin, Yabin; Bai, Ting; Wang, Fan

doi:10.1117/1.oe.54.12.123105

Cited by 6 publications

(3 citation statements)

References 11 publications

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“…The identifier text discussed in this article can only appear in the white layer, so formula ( 4) is modified, and the modified formula is given by formula (6).…”

Section: Image Segmentation Methods Based On Local Statistical Featuresmentioning

confidence: 99%

“…The texture-based sparse code is connected with the color feature to recognize the clothing style through the support vector machine (SVM) model. A series of experiments were carried out to analyze the characteristic attributes for clothing recognition [6]. Yang detects clothing regions by fusing superpixel segmentation, saliency detection and Gaussian Mixture Model (GMM).…”

Section: Introductionmentioning

confidence: 99%

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Clothing Style Recognition Method Based on Digital Image Processing

2021

IJFS

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The use of digital image processing technology to identify clothing styles from clothing images has broad application potential in clothing consumption analysis, auxiliary clothing design and identity recognition. In the current clothing style recognition field for feature extraction and classification of clothing contours, the main methods are extreme learning machine classification based on wavelet Fourier descriptor, and Euclidean distance classification based on fusion features. However, these methods also have some shortcomings. Currently, there is still no effective method to extract features and classify clothing contours. In order to solve this problem, this paper is based on the SVM classification method of Fourier contour description features. The contour curvature characteristic point in the figure can be described as the bending characteristic of the clothing contour curve, and its calculation is simple and intuitive, which improves the judgment effect of the similarity performance of the Hausdorff distance. This paper constructs a multi-resolution framework of the new image, uses edge detection algorithms to obtain the edges of each level of resolution image, and expands them into narrow edge bands, and combines the point distribution model with the edge narrow bands obtained by edge detection to perform multi-resolution image ASM search for. This paper proposes an image fusion algorithm based on algebraic multigrid and adaptive block. Because the coarse grid extracted by the algebraic multi-grid method can extract the detailed information of the image to a certain extent, the original image can be reconstructed from the grid data. Experimental research shows that from the overall recognition rate of various clothing styles, the Fourier descriptor has a high recognition rate for each clothing, and the stability of multiple experiments is also good.

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“…The identifier text discussed in this article can only appear in the white layer, so formula ( 4) is modified, and the modified formula is given by formula (6).…”

Section: Image Segmentation Methods Based On Local Statistical Featuresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Clothing Style Recognition Method Based on Digital Image Processing

2021

IJFS

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“…However, the current retina-like image sensors [19], [20] based on space-variant array structure are unsuitable to be applied directly in adaptive GI because the pixel size cannot be changed when the sensor parameters are specified. Alternatively, DMD, the core device of the CGI, can not only reach high frame rates up to 22 kHz but also achieve adaptive sampling because sampling patterns are easily programmable in accordance with different scenes.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Simulations of Retina-Like Three-Dimensional Computational Ghost Imaging

et al. 2019

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A retina-like 3-D (three-dimensional) computational ghost imaging (R-3DCGI) is proposed to obtain high resolution while maintaining high imaging efficiency. R-3DCGI models are developed, and corresponding simulations are conducted to verify and evaluate the accuracy and features of the R-3DCGI. Results show that the models obtain rotation and scaling invariances and compress redundant information, thereby improving imaging efficiency over the traditional computational ghost imaging. The relationships between parameters of the retina-like models and signal-noise ratio are discussed to optimize the retina-like structures in various applications.

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