Image Processing Based Proposed Drone for Detecting and Controlling Street Crimes
Drone technology is being used for military, agriculture, aerial photography, surveillance, remote sensing and many more purposes. In this paper, drone plane is been tested to find accuracy in target detection and analysis the can be controlled by operator. Shape detection algorithms have criminals based on real time image processing techniques. handle the rest of controlling, monitoring and targeting image processing techniques and 2nd processing unit will kilometers and it will automatically perform all operations and Operations of proposed plane controlled with two processing operations. Drone plane will monitor circular area of 5 processing time before implementing in such environment and proposed for monitoring and targeting the street crime results provide optimal accuracy in matching weapons type units, 1st processing unit is for implementation of real time
with name and shape in predefined database.
Shape detection is used by Anna  for people and vehicle detection in many real time image processing applications like as unmanned aerial vehicle (UAV) detection. Solar energy based drone was designed and tested by Philipp Oettershagen . Test was conducted in different weather conditions (like cloudy) and different seasons. The power measurement of flight was 12h 12min powered by solely batteries and the power performance was also tested for night. Other author presented effective work in , the battery swapping process for quadcopter UAVs because charging of UAVs must take long time about 45 minutes, which can delayed the given task. Many researchers have introduced several innovative techniques to stop or minimize number of crimes or can be used in war as Humvee is well known example of this technology. An operator based vehicle model has been suggested for controlling crimes, controlled from the base station using the short-range wireless network and also via satellite communication for long distance
The proposed vehicle is used for monitoring of the criminals using video cameras which are embedded in vehicle and target the criminals via guns which are also embedded in the vehicle. This work is useful for the affected areas where police or
security cannot access easily and the life of soldiers and officers on the risk. So for this purpose the use of autonomous vehicle and autonomous drone is very significant. As compare to automated vehicle UAV is faster, reliable, and unapproachable by criminals, cost effective, automatic and secure. It has better efficiency than automated vehicle. The proposed model contain more advantages from previous drone plane with providing automatic control, real time object analysis, decision making, monitoring and targeting. This is very innovative proposal to reduce the crime rate under complex environment or congested corridors
In this paper we proposed real time decision and targeting drone plane based on feature extraction and classification techniques. The design of proposed drone plane is based on two computational units for image processing and controlling operations. Bag of features approach was tested for weapon recognition with predefined database which performance is optimal and HOG is implemented for weapon detection and SVM is used for classification. In future we will analyze shadow regions in image to improve the accuracy of detection under shadow regions and occlusions because objects visualization under shadow regions makes difficult to detect or classify objects. Activity recognition in crime scene is also help to make accurate decision in real time situations so in future we will also emphasis on the activity recognition in crime scenes. Image classification for this proposed model can be made more efficient by increasing the number of image sets, decreasing processing time and enhancing the average accuracy.
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