Feature Edge Extraction for Human Body Cut Injured Detection using Deep Learning


  • Chandrashekhar Kumar, T. Muthumanickam


Human Body, Deep Learning, Cut Edge Detection, Image Processing, Convolution Neural Network, Contour Image.


In recent endeavours, the management style of medical patient treatment has been growing continuously. In the meantime, trends demand more accuracy and work performance beyond the level of advancement for waiting in line in hospitals, ending with emergency cases as well. To overcome the delay in response from the hospital end with medical high demand, the doctor-patient ratio is also around 1:700. And the need for blood in a human case is a little crucial based on the blood group. Also, to avoid this scenario and save human lives, we have to implement blood detection on the spot using the image processing technique with deep learning, which can close the gap between the arrangement of the blood bank system and human blood safety support with the patient as well. The current study can only be done after reaching the hospital; using various research attempts to fill this gap. But delay is still needed to reach proper support with advanced technology. To extract the image of blood colour detection using an optical clamp-on Sensor(OCS) deep learning blood detection and amount of blood flow based on healthy body range of blood status with a range of 5 litters for the adult body with advanced BMI technology.


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Lingyan Jiang, Jian Yao2, Baopu Li,Fei Fang, Qi Zhang, Max Q.-H. Meng,” Automatic Body Feature Extraction from Front and Side Images”. A Journal of Software Engineering and Applications, 2012,5,94-100 doi:10.4236/jsea.2012.512b019.

S.A. Rahman, S.-Y. Cho and M.K.H. Leung, “Recognising human actions by analyzing negative spaces,” IET Computer Vision, Vol. 6, No. 3, 2012, pp. 197–213. doi: 10.1049/iet-cvi.2011.0185

N. Ikizler and D.A. Forsyth, “Searching for complex hu-man activities with no visual examples,” Int. Journal of Compute. Vision, Vol. 80, No. 3, 2008, pp. 337–357. doi: 10.1007/s11263-008-0142-8.

C. Bregler, “Learning and recognizing human dynamics in video Sequences,” Proc. Computer Vision and Pattern Recognition, San Juan, 1997, pp. 568–574.

J.M. Lu and M.J. Wang, “Automated data collection using 3D whole body scanner,” Expert Systems with Applications, Vol. 35, No. 1-2, 2008, pp. 407–414. doi: 10.1016/j.eswa.2007.07.008.

P. Meunier and S. Yin, “Performance of a 2D image-based anthropometric measurement and clothing sizing system,” Applied Ergonomics, Vol. 31, No. 5, 2000, pp. 445–451. doi:10.1016/S0003-6870(00)00023-5.

H. Freeman, “On the encoding of arbitrary geometric con-figuration,” IRE Transactions on Electronics Computers, Vol. EC-10, No. 2, 1961, pp. 264–268. doi:10.1109/TEC.1961.5219197.

H. Freeman and L.S. Davis, “A corner-finding algorithm for chain-coded curves,” IEEE Transactions on Computers, Vol. C-26, No. 3, 1977, pp. 297–303. doi:10.1109/TC.1977.1674825.

J. Canny, “A computational approach to edge detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 8, No. 6, 1986, pp. 679-698. doi:10.1109/TPAMI.1986.4767851.

Y.L. Lin and M.J. Wang, “Constructing 3D Human Model from 2D images,” Int. Conf. on Industrial Engineering and Engineering Management, Xiamen, Oct, 2010, pp.1902-1906.

Y.L. Lin and M.J. Wang, “Constructing 3D human model from front and side images,” Expert Systems with application, Vol. 39, No. 5, April 2012, pp. 5012–5018. doi:10.1016/j.eswa.2011.10.011.

Y.L. Lin and M.J. Wang, “Automatic Feature Extraction from Front and Side Images,” Int. Conf. on Industrial Engineering and Engineering Management, Singapore, Dec, 2008, pp. 1949-1953.

Y.L. Lin and M.J. Wang, “Automated body feature ex-traction from 2D images,” Expert Systems with Applications, Vol. 38, No. 3, 2011, pp. 2585–2591. doi:10.1016/j.eswa.2010.08.048.

A. Ali and J.K. Aggarwal, “Segmentation and recognition of continuous human activity,” Proc. IEEE Workshop on Detection & Recog. of Events in Video, Vancouver, BC, 2001, pp. 28–35.

M. Kouchi and M. Mochimaru, “Errors in land marking and the evaluation of the accuracy of traditional and 3D anthropometry,” Applied Ergonomics, Vol. 42, No. 3, 2011, pp. 518-527. doi:10.


Iat-Fai Leong, “A study of automatic anthropometry and construction of computer manikins,” Master's thesis of National Cheng Kung University, 1992. (In Chinese)

ISO8559-1989 garment construction and anthropometric surveys body dimensions.

GB/T16160-2008 location and method of anthropometric surveys for garment.

D. K. Yadav, Renu, Ankita and I. Anjum, "Accident Detection Using Deep Learning," 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), Greater Noida, India, 2020, pp. 232-235, doi: 10.1109/ICACCCN51052.2020.9362808.

T. Jaspar Vinitha Sundari, J. G. Aswathy and S. Jayakamali, "Accident Detection and Severity Analysis using Deep Learning," 2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), Coimbatore, India, 2021, pp. 1-5, doi: 10.1109/


Greg Mori, Xiaofeng Ren, Alexei A. Efros and Jitendra Malik, “Recovering human body configurations: combining segmentation and recognition,” in Proc. IEEE Computer. Soc. Conf. Computer. Vision and Pattern Recogn., vol. 2, pp. 326-333, 2004.

Qingjie Sun, Enhua Wu, “Probability estimation for people detection,” International Journal of WSCG, 1(3):448-455, 2003

P. F. Felzenszwalb and D. P. Huttenlocher, “Efficient matching of pictorial structures,” in Proc. IEEE Computer. Soc. Conf. Comput. Vision and Pattern Recogn., 2000.

S. Ioffe and D. Forsyth, “Probabilistic methods for finding people,” International Journal of Computer Vision, 43(1):45-68, Jun. 2001.

Carsten Rother, Vladimir Kolmogorov and Adrew Blake, “GrabCut-Interactive foreground extraction using iterated Graph Cuts,” in ACM Transactions on Graphics (SIGGRAPH’04), August 2004.

Yuri Y. Boykov and Marie-Pierre Jolly, “Interactive graph cuts for optimal boundary and region segmentation of objects in N-D images,” in Proc IEEE Int. Conf. On Computer Vision, July 2001.

Vladimir Vezhnevets, Vassili Sazonov and Alla Andreeva, “A survey on pixel-based skin detection techniques,” in Proceedings of the Graphicon-Moscow, pp. 85-92, September 2003.

Orchard, M.T., and Bounman, C.A. “Color quantization of images,” IEEE Transactions on Signal Processing, Vol.39, No.12, pp.2677-2690, 1991.

Yuri Boykov and Vladmir Kolmogorov, “An experimental comparison of Min-Cut/Max-Flow algorithms for energy minimization in vision,” IEEE Transactions on PAMI, Vol.26, No.9, pp.1124-1137, Sept. 2004.

Stella X.Yu, Ralph Cross and Jianbo Shi, “Concurrent object recognition and segmentation by graph partitioning”, in NIPS’02, November, 2002.




How to Cite

Chandrashekhar Kumar. (2024). Feature Edge Extraction for Human Body Cut Injured Detection using Deep Learning. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 1850–1856. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5755



Research Article