Open Access
ARTICLE
The Crime Scene Tools Identification Algorithm Based on GVF‐Harris‐SIFT and KNN
Nan Pan1, Dilin Pan2, Yi Liu2
1 Faculty of Civil Aviation and Aeronautical, Kunming University of Science & Technology, Kunming 650500, P.R. China
2 Kunming SNLab Tech Co., Ltd., Kunming 650228, P.R. China
* Corresponding Author: Nan Pan,
Intelligent Automation & Soft Computing 2019, 25(2), 413-419. https://doi.org/10.31209/2019.100000103
Abstract
In order to solve the cutting tools classification problem, a crime tool
identification algorithm based on GVF-Harris-SIFT and KNN is put forward. The
proposed algorithm uses a gradient vector to smooth the gradient field of the
image, and then uses the Harris angle detection algorithm to detect the tool
angle. After that, the descriptors of the eigenvectors in corresponding feature
points were using SIFT to obtained. Finally, the KNN machine learning
algorithms is employed to for classification and recognition. The experimental
results of the comparison of the cutting tools show the accuracy and reliability
of the algorithm.
Keywords
Cite This Article
N. Pan, D. Pan and Y. Liu, "The crime scene tools identification algorithm based on gvf‐harris‐sift and knn,"
Intelligent Automation & Soft Computing, vol. 25, no.2, pp. 413–419, 2019. https://doi.org/10.31209/2019.100000103