Max-Plus Algebra-Based Morphological Wavelet Transform Watermarking for Highly-Parallel Processing with Mobile Embedded Processor

Kumaki, Takeshi; Murakami, Yuma; Itaya, Shuhei; Nakao, Ken–ichi; Ogura, Takeshi; Fujino, Takeshi

doi:10.2299/jsp.16.547

Cited by 9 publications

(6 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The value of α is chosen by considering the trade-off between image quality and extraction accuracy. On the basis of experiments with several values of α, we have found that 5 is a practical value for α [2], [21].…”

Section: Improved Algorithmmentioning

confidence: 99%

“…The MMT algorithm has been focused on to achieve both high quality and high compression in fast image processing on mobile embedded processors [1], [2], [4], [15]- [18]. This transform has rich potential for effective directional image coding according to these studies.…”

Section: Algorithmmentioning

confidence: 99%

“…This is because, in the case of embedding information data in digital contents for mobile applications, real-time processing speed is more important than data security and image quality. With this background, we report max-plus algebra-based morphological wavelet transform (MMT) watermarking as a novel data-embedding algorithm for highly parallel processing with a mobile embedded processor [2], [18], [21]. Figure 18 shows the watermarking flow using the MMT for the case of a 2 × 2 pixel sampling window.…”

Section: Algorithmmentioning

confidence: 99%

“…The adaptive multidirectional max-plus algebra-based morphological wavelet transform (AM-MMT) captures directional features of objects in an image for data compression [6]. MMT watermarking is a data-embedding algorithm for highly parallel processing [2]. The morphological pattern spectrum used for detecting image manipulation extracts information on target objects in an image and detects several image manipulations [3]- [5].…”

mentioning

confidence: 99%

See 3 more Smart Citations

Morphological Methods in Image Processing for Embedded Processors

Kumaki

Fujita

Fujino

et al. 2018

Journal of Signal Processing

Self Cite

View full text Add to dashboard Cite

This paper reports studies conducted on image processing with morphological methods. Morphological methods are based on mathematical morphology. These methods can analyze the spatial structure and shape of objects in a target image. We focused on the effectiveness of morphological methods for image processing on embedded processors. Several studies on this topic have been conducted and reported in [1]- [6]. The max-plus algebra-based morphological wavelet transform (MMT) is suitable for parallel processing on simple low-power embedded processors [1]. The adaptive multidirectional max-plus algebra-based morphological wavelet transform (AM-MMT) captures directional features of objects in an image for data compression [6]. MMT watermarking is a data-embedding algorithm for highly parallel processing [2]. The morphological pattern spectrum used for detecting image manipulation extracts information on target objects in an image and detects several image manipulations [3]- [5]. Research on these topics opens up potential for various applications of morphological methods. We plan to continue research on morphological-method-based image-processing algorithms for embedded processors.

show abstract

Section: Improved Algorithmmentioning

confidence: 99%

Section: Algorithmmentioning

confidence: 99%

Section: Algorithmmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Morphological Methods in Image Processing for Embedded Processors

Kumaki

Fujita

Fujino

et al. 2018

Journal of Signal Processing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Consequently, the algorithm for the MMT is assumed to be suitable for embedded low-power processors. Utilizing these features, MMT watermarking has been proposed for mobile embedded devices in our papers [9], [10]. Figure 1 shows the watermarking flow using the MMT for a 2 × 2 pixel sampling window…”

Section: Max-plus Algebra-based Morphological Wavelet Transform Watermentioning

confidence: 99%

Development of Compression Tolerable and Highly Implementable Watermarking Method for Mobile Devices

Kumaki

Nakao

Hozumi

et al. 2014

IEICE Trans. Inf. & Syst.

Self Cite

View full text Add to dashboard Cite

SUMMARYThis paper reports on the image compression tolerability and high implementability of a novel proposed watermarking method that uses a morphological wavelet transform based on max-plus algebra. This algorithm is suitable for embedded low-power processors in mobile devices. For objective and unified evaluation of the capability of the proposed watermarking algorithm, we focus attention on a watermarking contest presented by the IHC, which belongs to the IEICE and investigate the image quality and tolerance against JPEG compression attack. During experiments for this contest, six benchmark images processed by the proposed watermarking is done to reduce the file size of original images to 1/10, 1/20, or less, and the error rate of embedding data is reduced to 0%. Thus, the embedded data can be completely extracted. The PSNR value is up to 54.66 dB in these experiments. Furthermore, when the smallest image size is attained 0.49 MB and the PSNR value become about 52 dB, the proposed algorithm maintains very high quality with an error rate of 0%. Additionally, the processing time of the proposed watermarking can realize about 416.4 and 4.6 times faster than that of DCT and HWT on the ARM processor, respectively. As a result, the proposed watermarking method achieves effective processing capability for mobile processors.

show abstract

Multi-image Enhancement Technique Using Max-Plus Algebra-Based Morphological Wavelet Transform

Kannoth

Kumar²

2019

Communications in Computer and Information Science

View full text Add to dashboard Cite

Max-Plus Algebra-Based Morphological Wavelet Transform Watermarking for Highly-Parallel Processing with Mobile Embedded Processor

Cited by 9 publications

References 11 publications

Morphological Methods in Image Processing for Embedded Processors

Morphological Methods in Image Processing for Embedded Processors

Development of Compression Tolerable and Highly Implementable Watermarking Method for Mobile Devices

Multi-image Enhancement Technique Using Max-Plus Algebra-Based Morphological Wavelet Transform

Contact Info

Product

Resources

About