An algorithm combined with color differential models for license-plate location

Tian, Yuanmei; Song, Juan; Zhang, Xiangdong; Shen, Peiyi; Zhang, Liang; Gong, Weibo; Wei, Wei; Zhu, Guangming

doi:10.1016/j.neucom.2016.02.081

Cited by 18 publications

(7 citation statements)

References 15 publications

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“…Principle component analysis (PCA) is used to analyze the surface reflectance of Munsell color blocks. It is pointed out that the spectral reflectance expressed by the first three feature vectors is 99% consistent with the actual measured reflectance [24][25][26], which proves that the spectral reflectance function of most objects is bandwidth-limited, and the spectral reflectance can be represented by three feature vectors [27][28][29][30].…”

Section: Related Workmentioning

confidence: 75%

[Retracted] Using Color Difference Compensation Method to Balance and Repair the Image of Art Design

Ji¹,

Shang

2021

Complexity

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In the case of complex illumination background, the image has fuzziness and chromatic aberration, which can improve the imaging effect of the image by white balance chromatic aberration compensation. The traditional method uses the contour feature fusion adaptive matching method to compensate the white balance under the complex illumination background, which leads to the good color difference compensation effect when the image pixel is low. A white balance color compensation algorithm for fuzzy chromatic aberration based on wavelet packet decomposition is proposed. The original image was denoised and filtered. The white balance characteristics of the image were analyzed and extracted based on the wavelet packet decomposition method, and the adaptive balance design was carried out to realize the white balance and color difference compensation of the art design chromatic aberration image. By using the known pixel information of the image block to be repaired, the statistical properties of the image block to be repaired are predicted, and the matching cost of the image block to be matched that meets the restriction conditions is calculated. By introducing the objective factor, the matching cost function is improved to balance the restoration process, and the unnatural problem caused by the repeated appearance of some image details in the restoration results is solved. The simulation results show that the method can effectively balance the color difference of the image, improve the aesthetic feeling of the image, and improve the performance of the detail features of the image. The peak signal-to-noise ratio is high.

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Section: Related Workmentioning

confidence: 75%

[Retracted] Using Color Difference Compensation Method to Balance and Repair the Image of Art Design

Ji¹,

Shang

2021

Complexity

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“…Jun et al [ 25 ] present a morphology-based method for LPD by extracting contrast features. To solve illumination variation and background interference, Tian et al [ 1 ] propose an Adaboost algorithm combined with a color differential model, which can detect the license plate in a coarse-to-fine manner. The literature [ 4 , 26 ] propose to use the edge and texture features for license plate detection.…”

Section: Related Workmentioning

confidence: 99%

“…Recent LPD methods can be roughly divided into direct and indirect ways. Direct methods directly localize the license plate in the input image with handcrafted features [ 1 , 2 , 3 , 4 ], deep-learning features [ 5 , 6 , 7 , 8 , 9 ], or license plate recognition system [ 10 , 11 ]. However, detecting small-sized license plates is challenging since they only occupy a relatively small area in the whole image.…”

Section: Introductionmentioning

confidence: 99%

Scale-Invariant Multidirectional License Plate Detection with the Network Combining Indirect and Direct Branches

Chen

Liu

et al. 2021

Sensors

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As the license plate is multiscale and multidirectional in the natural scene image, its detection is challenging in many applications. In this work, a novel network that combines indirect and direct branches is proposed for license plate detection in the wild. The indirect detection branch performs small-sized vehicle plate detection with high precision in a coarse-to-fine scheme using vehicle–plate relationships. The direct detection branch detects the license plate directly in the input image, reducing false negatives in the indirect detection branch due to the miss of vehicles’ detection. We propose a universal multidirectional license plate refinement method by localizing the four corners of the license plate. Finally, we construct an end-to-end trainable network for license plate detection by combining these two branches via post-processing operations. The network can effectively detect the small-sized license plate and localize the multidirectional license plate in real applications. To our knowledge, the proposed method is the first one that combines indirect and direct methods into an end-to-end network for license plate detection. Extensive experiments verify that our method outperforms the indirect methods and direct methods significantly.

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“…Those points concentrated near the plate regions would negatively affect the location results. Thus, mathematical morphology operation [25,26] can be applied to the edge intensity images to extract the license plate through the following steps. (i) Obtaining candidate LP regions by morphological filtering method.…”

Section: Morphological Filtering and Lp Screeningmentioning

confidence: 99%

Fast Cartoon-Texture Decomposition Filtering Based License Plate Detection Method

Wang

Zhao

Liu

et al. 2018

Mathematical Problems in Engineering

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Vehicle license plate detection is an important step in automatic license plate recognition, which is prone to be influenced by the background interference and complex environment conditions. It is known that cartoon-texture decomposition split an image into geometric cartoon and texture component, which can remove background interference away from the vehicle image. In this paper, we introduce a fast cartoon-texture decomposition filter into the detection process. Combining the edge detection, morphological filtering and Radon transform based tilt correction method, we formulate a new license plate detection algorithm. Experiment results confirm that the proposed algorithm can remove background interference away, inhibit the emergence of fake license plates, and improve the detection accuracy. Moreover, there is no inner loop iteration in the new algorithm, so it is fast and high-efficiency.

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An algorithm combined with color differential models for license-plate location

Cited by 18 publications

References 15 publications

[Retracted] Using Color Difference Compensation Method to Balance and Repair the Image of Art Design

[Retracted] Using Color Difference Compensation Method to Balance and Repair the Image of Art Design

Scale-Invariant Multidirectional License Plate Detection with the Network Combining Indirect and Direct Branches

Fast Cartoon-Texture Decomposition Filtering Based License Plate Detection Method

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