Skip to main content

Advertisement

SpringerLink
Log in

Image search system and industrial product design based on CPU parallel computing

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

The goal of industrial product design is to market products that meet consumer needs, which specifies that the creative behavior of product design should be restricted by the market environment. The further integration of technology, design, and market is developing rapidly, and we need to shift the focus from art and design thinking to a favorable position that encompasses the entire society. The content-based image restoration technology analyzes the image according to the visual attributes and spatial position relationship of the image, such as color, texture, shape, etc., and creates an image feature vector database to reconstruct the image through image feature extraction. Nowadays, multi-core processors are everywhere. Parallel algorithms developed on multi-core CPUs are highly adaptable and can be used in most environments. By using parallel computing on a multi-core CPU, you can make full use of processor resources and improve resources. By improving and optimizing algorithms, parallel processing technology is used to increase the speed of image processing. Sparse image resolution algorithms and aircraft recognition methods use multi-core CPU parallel processing technology to increase processing speed and processing efficiency. Full-featured image search. This system effectively eliminates search restrictions through a function and improves search efficiency and search results. Accuracy. Finally, use the test data set to test the system and further optimize its performance. Combined with typical cases, analyze the close relationship between human vision, hearing, touch, movement, smell, etc. and product safety, and accept and summarize the safety principles of industrial product design.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Lowthian, J. A., et al. (2011). The challenges of population ageing: accelerating demand for emergency ambulance services by older patients, 1995–2015. Medical Journal of Australia, 194(11), 574–578.

    Article  Google Scholar 

  2. Maratea, A., Petrosino, A., & Manzo, M. (2013). Generation of description metadata for video files. In Proceedings of the 14th international conference on computer systems and technologies—CompSysTech’13 (Vol. 76, No. 7, pp. 262–269).

  3. Matejka, J., Grossman, T., & Fitzmaurice, G. (2014). Video lens: Rapid playback and exploration of large video collections and associated metadata. In Proceedings of the 27th annual ACM symposium on user interface software and technology, UIST’14, ACM, New York (Vol. 82, No. 9, pp. 541–550).

  4. Mazloom, M., et al. (2013). Querying for video events by semantic signatures from few examples. In Proceedings of the 21st ACM international conference on multimedia (vol. 68, No. 5, pp. 609–612).

  5. McCloskey, S., & Davalos, P. (2012). Activity detection in the wild using video metadata. Pattern recognition (ICPR), 58(7), 3140–3143.

    Google Scholar 

  6. McGinnis, S., & Moore, J. (2006). The impact of the aging population on the health workforce in the United States: summary of key findings. Cahiers de sociologie et de démographie, 28(6), 568–573.

    Google Scholar 

  7. Mehla, R., & Aggarwal, R. (2014). Automatic speech recognition: A survey. International Journal of Advanced Research in Computer Science and Electronics Engineering, 3(1), 45–53.

    Google Scholar 

  8. Metze, F., et al. (2013). Beyond audio and video retrieval: topic-oriented multimedia summarization. The International Journal of Multimedia Information Retrieval, 2(2), 131–144.

    Article  Google Scholar 

  9. Mihailidis, A., et al. (2008). The COACH prompting system to assist older adults with dementia through handwashing: an efficacy study. BMC Geriatrics 8(5), 28.

    Article  Google Scholar 

  10. O’Neill, S. A.. et al. (2010). Video reminders as cognitive prosthetics for people with dementia. Ageing International, 36(2), 267–282.

    Google Scholar 

  11. Panchal, P., Merchant, S., & Patel, N. (2012). Scene detection and retrieval of video using motion vector and occurrence rate of shot boundaries. In 2012 Nirma University international conference on engineering (NUiCONE) (Vol. 65, No. 9, pp. 1–6).

  12. Papadopoulos, D. P., et al. (2013). Automatic summarization and annotation of videos with lack of metadata information. Expert Systems with Applications, 40(14), 5765–5778.

    Article  Google Scholar 

  13. Patel, B. V., & Meshram, B. B. (2012). Content based video retrieval systems. International Journal of Ubiquitous Computing, 3(2), 13–30.

    Article  Google Scholar 

  14. Perea-Ortega, J. M., et al. (2013). Semantic tagging of video ASR transcripts using the web as a source of knowledge. Computer Standards & Interfaces, 35(5), 519–528.

    Article  Google Scholar 

  15. Rafferty, J., et al. (2014). Automatic summarization of activities depicted in instructional videos by use of speech analysis. In Pecchia L et al (eds) Ambient assisted living and daily activities. Lecture notes in computer science (Vol. 35, No. 8, pp. 123–130). Springer, New York.

  16. Rafferty, J., et al. (2014). NFC based provisioning of instructional videos to assist with instrumental activities of daily living. In 2014 36th annual international conference of the IEEE engineering in medicine and biology society, EMBC (Vol. 56, nN. 8, pp. 4131–4134).

  17. Rafferty, J., Chen, L., et al. (2015). Goal lifecycles and ontological models for intention based assistive living within smart environments. The Computer Systems Science and Engineering, 30(1), 7–18.

    Google Scholar 

  18. Rafferty, J., Nugent, C., et al. (2015). Automatic metadata generation through analysis of narration within instructional videos. Journal of Medical Systems, 39(9), 1–7.

    Article  Google Scholar 

  19. Shabani, A. H., Zelek, J. S., & Clausi, D. A. (2013). Multiple scale-specific representations for improved human action recognition. Pattern Recognition Letters, 34(15), 1771–1779.

    Article  Google Scholar 

  20. Yang, H., & Meinel, C. (2014). Content based lecture video retrieval using speech and video text information. IEEE Transactions on Learning Technologies 7(2), 142–154.

    Article  Google Scholar 

  21. Ababneh, J. I., Bataineh, M. H. (2008). Linear phase FIR filter design using p swarm optimization and genetic algorithms. Digital Signal Process, 18(4), 657–668.

    Article  Google Scholar 

  22. Aziz, M. A. E., Ewees, A. A. , Hassanien, A. E. (2018). Multi-objective whale optimization algorithm for content-based image retrieval. Multimed Tools, 77(4), 26135–26172.

    Article  Google Scholar 

Download references

Acknowledgements

Zhejiang Provincial Education Planning Research Projects “Five Points-Five Methods, Teaching Paradigm Construction and Research of Design Innovative Thinking” (2020SCG381). The General Research Program of Medicine and Hygiene from the Health and Family Planning Commission in Zhejiang Province “Study on Inflammatory and other Biomarkers’ Role in Pathophysiology and Prediction of Gestational Diabetes Mellitus” (2021KY746).

Author information

Authors and Affiliations

  1. Creative Design Manufacturing Collaborative Innovation Center, China Academy of Art, Hangzhou, 310024, Zhejiang, China

    Li He, Zhefang Hu & Yang Yu

  2. Departments of Nutrition, Sir Run Run Shaw Hospital, School of Medicine Zhejiang University, Hangzhou, 310020, Zhejiang, China

    Zhefang Hu

  3. Information Engineering School, Dianzi University, Hangzhou, 311305, China

    Yang Yu

Authors
  1. Li He
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhefang Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yang Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Li He.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

He, L., Hu, Z. & Yu, Y. Image search system and industrial product design based on CPU parallel computing. Wireless Netw (2021). https://doi.org/10.1007/s11276-021-02680-5

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11276-021-02680-5

Keywords

Search

Navigation