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An Image Processing Approach to Blood Spatter Source Reconstruction

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Intelligent Computing and Information and Communication

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 673))

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Abstract

Blood spatter analysis is a part of Criminal Justice system and subpart of the forensic science. Traditional blood spatter analysis has a problem with the crime scene contamination. The crime scene contamination can led to the unacceptance of the evidences. The blood spatter analysis is the process which heavily relies on the expertise of the forensic scientist. The human intervention also creates the problem of errors and misjudgments. Use of image processing to the whole will deal with automation of removing human factor. The proposed method takes the image from blood spatter using image processing and reconstructs the source of the blood. The proposed methodology uses the Otsu’s method for thresholding and Hough transform for edge detection.

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References

  1. Anita Wonder BS, “Blood Dynamics”, Anita Y. Wonder, Academic Press, 2001 ISBN-10: 0127624570, 1st edition August 2001, pp. 36–51.

    Google Scholar 

  2. P. Joris, W. Develter, E. Jenar, D. Vandermeulen, W. Coudyzer, J. Wuestenbergs, B. De Dobbelaer, W. Van de Voorde, E. Geusens, P. Claes, “A novel approach to automated bloodstain pattern analysis using an active bloodstain shape model”, Journal of Forensic radiology and image, Volume 2, Issue 2, April 2014 pp. 95.

    Google Scholar 

  3. Abhijit Shinde, Dr. Deepali Sale, “Blood Spatter Trajectory Analysis for Spatter Source Recognition Using Image Processing”, 2016 IEEE Conference on Advances in Signal Processing (CASP), Cummins College of Engineering for Women, Pune, pg. 375–380, Jun 9–11, 2016, DOI: 10.1109/CASP.2016.774619934-39.

    Google Scholar 

  4. Abhijit Shinde, Dr. Deepali Sale, “Blood Spatter Source Reconstruction Using Image Processing”, IETE National Journal of Innovation and Research (NJIR), ISSN 2320–8961, Volume III, Issue II, December 2015.

    Google Scholar 

  5. Giovanni Acampora, Autilia Vitiello, Ciro Di Nunzio, Maurizio Saliva, Luciano Garofano, “Towards Automatic Bloodstain Pattern Analysis through Cognitive Robots”, conference—IEEE International Conference on Systems, Man, and Cybernetics, 2015.

    Google Scholar 

  6. Wen-Yuan Chen, Yan-Chen Kuo, Chen-Chung Liu and Yi-Tsai Chou, “Region-Based Segmentation Algorithm for Color Image Using Generated Four-Connectivity and Neighbor Pixels Comparing Criterion”, Proceedings of the 2005 Workshop on Consumer Electronics and Signal Processing, 2005.

    Google Scholar 

  7. G. Gordon, T. Darrell, M. Harville, J. Woodfill, “Background estimation and removal based on range and color”, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, (Fort Collins, CO), June 1999.

    Google Scholar 

  8. Robert A. McLaughlin, Technical Report, “Randomized Hough Transform: Improved Ellipse Detection with Comparison”, University of Western Australia, 1997.

    Google Scholar 

  9. H. K. Yuen, J. Illingworth, J. Kittler, “Detecting partially occluded ellipses using the Hough transform”, Image and Vision Computing—4th Alvey Vision Meeting archive, Volume 7 Issue 1, February 1989, pp. 31–37.

    Google Scholar 

  10. Yonghong Xie; Dept. of Comput. Sci., Nevada Univ., Reno, NV, USA; Qiang Ji, “A new efficient ellipse detection method”, Pattern Recognition, 2002. Proceedings 16th International Conference on (Volume: 2), 2002, pp. 957–960.

    Google Scholar 

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Disclaimers

The fake blood used for experimentation was made up of non-animal food products such as corn syrup, sugar, coco-powder, and artificial food coloring. The resulting product is usually used for forensic experiments. No human being or animal was harmed for the experiment. The procedure for generating blood spatter is similar to one followed by many other authors [1, 2].

Author information

Authors and Affiliations

  1. Bhima Institute of Management and Technology, Kagal, Kolhapur, 416202, India

    Abhijit Shinde

  2. Sinhgad College of Engineering, Pune-41, Maharashtra, India

    Ashish Shinde

  3. Dr. D. Y. Patil Institute of Engineering Technology, Pimrpi, Pune- 18, India

    Deepali Sale

Authors
  1. Abhijit Shinde
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  2. Ashish Shinde
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  3. Deepali Sale
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Corresponding author

Correspondence to Abhijit Shinde .

Editor information

Editors and Affiliations

  1. Department of Computer Software, University of Aizu, Aizuwakamatsu, Fukushima, Japan

    Subhash Bhalla

  2. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. Department of Information Technology, MIT College of Engineering, Pune, Maharashtra, India

    Anjali A. Chandavale

  4. Department of Information Technology, MIT College of Engineering, Pune, Maharashtra, India

    Anil S. Hiwale

  5. Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, India

    Suresh Chandra Satapathy

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© 2018 Springer Nature Singapore Pte Ltd.

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Cite this paper

Shinde, A., Shinde, A., Sale, D. (2018). An Image Processing Approach to Blood Spatter Source Reconstruction. In: Bhalla, S., Bhateja, V., Chandavale, A., Hiwale, A., Satapathy, S. (eds) Intelligent Computing and Information and Communication. Advances in Intelligent Systems and Computing, vol 673. Springer, Singapore. https://doi.org/10.1007/978-981-10-7245-1_16

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  • DOI: https://doi.org/10.1007/978-981-10-7245-1_16

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7244-4

  • Online ISBN: 978-981-10-7245-1

  • eBook Packages: EngineeringEngineering (R0)

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