%0 Journal Article %1 bhavya2023fingerprint %A Bhavya, %A Nalini, %A Deepika, %A Nagaraj, %A Jagadamba, %D 2023 %J International Journal of Innovative Research in Information Security %K crime detection fingerprint identification image %N 2 %P 10-14 %R 10.26562/ijiris.2023.v0902.02 %T Fingerprint Image Identification for Crime Detection %U http://www.ijiris.com/volumes/Vol09/iss-02/02.MYIS10081.pdf %V 9 %X The identification of a person has become, crucial part in this physical world (fast growing) identification features of a person can be included iris, Fingerprints etc. The fingerprint plays an important role in crime investigation, to identify the criminals which makes easy to solve the crime. The fingerprint is collected from the crime scene. These images are stored in digital format saved in database. The image is pre-processed using techniques acquisition, Enhancement, Thinning fingerprint image features are extracted from the pre-processed image. These pre-processed data is tested and trained by CNN model using random forest and decision trees these algorithms, Algorithm identifies the criminals based on matching accuracy.

@article{bhavya2023fingerprint, abstract = {The identification of a person has become, crucial part in this physical world (fast growing) identification features of a person can be included iris, Fingerprints etc. The fingerprint plays an important role in crime investigation, to identify the criminals which makes easy to solve the crime. The fingerprint is collected from the crime scene. These images are stored in digital format saved in database. The image is pre-processed using techniques acquisition, Enhancement, Thinning fingerprint image features are extracted from the pre-processed image. These pre-processed data is tested and trained by CNN model using random forest and decision trees these algorithms, Algorithm identifies the criminals based on matching accuracy.}, added-at = {2023-05-30T08:25:19.000+0200}, author = {Bhavya and Nalini and Deepika and Nagaraj and Jagadamba}, biburl = {https://www.bibsonomy.org/bibtex/2f9bbe6c6812d90aca581b4d9f1025d56/ijiris}, description = {Fingerprint identification system used to identify the criminal who involved in the crime helps to automate fingerprint identification process. Pre-processing was performed with Otsu thresholding, fingerprint thinning, feature extraction is done using minutiae algorithm and GLCM method. The training is done using Random Forest and Decision tree algorithm and Random gives more accuracy than Decision Tree with accuracy more than 80%. }, doi = {10.26562/ijiris.2023.v0902.02}, interhash = {6f69105d51b937414a9614c3ba01b4b4}, intrahash = {f9bbe6c6812d90aca581b4d9f1025d56}, issn = {2349-7017}, journal = {International Journal of Innovative Research in Information Security}, keywords = {crime detection fingerprint identification image}, language = {English}, month = {May 2023}, note = {[1]. Adler, A.; Schuckers, S. Biometric vulnerabilities, overview. In Encyclopedia of Biometrics; Li, S.Z., Jain, A., Eds.; Springer: Boston, MA, USA, 2009. https://doi.org/10.1007/978-0-387-73003-5_65 [2]. Nguyen, H.T. Fingerprints Classification through Image Analysis and Machine Learning Method. Algorithms 2019, 12, 241. https://doi.org/10.3390/a12110241 [3]. Biometric Systems Lab—FVC2000: Fingerprint Verification Competition. Available online: FVC2000 (unibo.it)(accessed on 22 January 2021). [4]. Tang, Y.; Gao, F.; Feng, J. Latent fingerprint minutia extraction using fully convolutional network. In Proceedings of the 2017 IEEE International Joint Conference on Biometrics, Denver, CO, USA, 1–4 October 2017; pp. 117–123. https://doi.org/10.1109/btas.2017.8272689 [5]. Huang, X.; Qian, P.; Liu, M. Latent fingerprint image enhancement based on progressive generative adversarial network. In Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, Seattle, WA, USA, 14–19 June 2020; pp. 3481–3489. https://doi.org/10.1109/cvprw50498.2020.00408 [6]. Neurotechnology Company—Sample Fingerprint Databases. Available online: Download biometric algorithm demo software, SDK trials, product brochures. (neurotechnology.com)(accessed on 22 January 2021). [7]. Fingerprint Image identification for crime detection (2019) Fingerprint Image Identification for Crime Detection | IEEE Conference Publication | IEEE Xplore https://doi.org/10.1109/iccsp.2019.8698014}, number = 2, pages = {10-14}, timestamp = {2023-05-30T08:26:43.000+0200}, title = {Fingerprint Image Identification for Crime Detection}, url = {http://www.ijiris.com/volumes/Vol09/iss-02/02.MYIS10081.pdf}, volume = 9, year = 2023 }