A Practical Animal Detection and Collision Avoidance System Using Computer Vision Technique

ABSTRACT:

One serious problem that all the developed nations are facing today is death and injuries due to road accidents. The collision of an animal with the vehicle on the highway is one such big issue which leads to such road accidents. In this paper, a simple and a low-cost approach for automatic animal detection on highways for preventing animal-vehicle collision using computer vision techniques are proposed. A method for finding the distance of the animal in real-world units from the camera mounted vehicle is also proposed. The proposed system is trained on more than 2200 images consisting of positive and negatives images and tested on various video clips of animals on highways with varying vehicle speed. As per the two-second rule, our proposed method can alert the driver when the vehicle speed is up to 35 kmph. Beyond this speed, though the animal gets detected correctly, the driver doesn’t get enough time to prevent a collision. An overall accuracy of almost 82.5% is achieved regarding detection using our proposed method.

PROJECT OUTPUT VIDEO:

EXISTING SYSTEM:

• A recent study in the existing system shown that human beings have to take the final call while driving whether they can control their car to prevent collision with a response time of 150ms or no.

• Some scientific researchers have proposed a method that requires the animals to take a pose towards the camera for the trigger, including face detection.

• Animals can be detected using the knowledge of their motion. The fundamental assumption here is that the default location is static and can simply be subtracted. All blobs, which stay after the operation are measured as the region of interest. Although this technique performs well in controlled areas, e.g. underwater videos, it does not work universally, especially road or highway side videos.

• Researchers in the existing system used threshold segmentation approach for getting the targeted animal’s details from the background. Recent researches also revealed that it ‘s hard to decide the threshold value as the background changes often. A method applicable to moving backgrounds (e.g., due to camera motion) is presented in subsequent studies. The authors also state that other moving objects apart from the object of interest may be falsely detected as an animal.

DISADVANTAGES OF EXISTING SYSTEM:

• The issue with the existing system approach is that human eyes get exhausted quickly and need rest, which is why this method is not that effective.

• The problem with existing system technique is that face detection requires animals to see into the camera which is, not necessarily captured by the road travel video. Animals can arrive from a scene from various directions and in different sizes, poses, and color.

• Though various practical solutions for automatic lane detection and pedestrian detection on highways are available still research related to automatic animal detection on highways is going on.

• Animal detection in wildlife (forest) videos or underwater videos (controlled areas) have been tried in past but the challenges are much more when detecting animals on highways (uncontrolled areas) as both animal as well as a camera mounted vehicle is moving apart from other obstacles on the road which are also moving or stationary. There is no issue of speed (vehicle speed as well as animal speed) and detecting distance of animal from the vehicle in wildlife videos which is crucial and critical in animal detection on highways.

• The biggest challenge in detecting animals compared to pedestrians or other objects is that animals come in various size, shape, pose, color and their behavior is also not entirely predictable. Though the basic shape and size of a human being are pretty average and standard, the same is not true for animals.

• Although various methods and approaches have been used and are still in progress to detect, solve and reduce the number of animal-vehicle collisions, the absence of any practical systems related to an animal-vehicle collision on highways has delayed any substantial development in the scenario

PROPOSED SYSTEM:

• Intelligent highway safety and driver assistance systems are very helpful to reduce the number of accidents that are happening due to vehicle-animal collisions. On Indian roads, two types of animals – the cow and the dog are found more often than other animals on the road. The primary focus of the proposed work is for detection of animals on roads which can have the potential application of preventing an animal-vehicle collision on highways. Specific objectives of the research work are:

• To develop a low-cost automatic animal detection system in context to Indian roads.

• Finding the approximate distance of animal from the vehicle in which camera is mounted.

• To develop an alert system once the animal gets detected on the road which may help the driver in applying brakes or taking other necessary action for avoiding collision between vehicle and animal.

ADVANTAGES OF PROPOSED SYSTEM:

• Algorithm developed is working properly and able to detect an animal in different conditions on roads and highways.

• Estimation of animal distance from the testing vehicle is done. Maximum detecting distance of the animal from the camera mounted vehicle was found to be 20 meters.

• Speed analysis (different speeds like 20, 30, 35, 40, 50, 60 kmph) is implemented and tested.

• Alert signal to the driver is available

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

• System           : Pentium Dual Core.

• Hard Disk      : 120 GB.

• Monitor          : 15’’ LED

• Input Devices : Keyboard, Mouse

• Ram                : 1GB.

SOFTWARE REQUIREMENTS:

• Operating system : Windows 7.

• Coding Language : MATLAB

• Tool                       : MATLAB R2013A

REFERENCE:

S. Sharma, D. Shah, “A Practical Animal Detection and Collision Avoidance System Using Computer Vision Technique”, IEEE 2017.