Fast Human Recognition System on Real-Time Camera
DOI:
https://doi.org/10.26555/jiteki.v9i4.27009Keywords:
YOLO, Optimization, Image Processing, Computer Vision, Object DetectionAbstract
Technology development is very rapid, so all fields are required to develop technology to increase the effectiveness and efficiency of work. One of the focuses is related to image processing technology. We can get many benefits by implementing this system, so various fields have implemented image processing systems, such as security, health, and education. One of the current obstacles is in the area of safety, namely in the field of searching for people, which is still done manually. Often search teams find it challenging to find people because of the significant search area, low light conditions, and complex search fields. Therefore, we need a tool capable of detecting humans to assist in finding people. Therefore, to detect human objects, the authors try to research human object detection using a simple device for the human object detection system. The authors use the You only look once (YOLO) method with the YoloV4-Tiny type, where this algorithm has high detection speed and accuracy. Using the YOLOV4-Tiny simulation method for human object recognition, a detection rate of 100% is obtained with an FPS value of 5.Downloads
Published
2023-09-30
Issue
Section
Articles
License
Authors who publish with JITEKI agree to the following terms:
- Authors retain copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
This work is licensed under a Creative Commons Attribution 4.0 International License