FAST AND PROVABLY ACCURATE FIRE DETECTION USING IMAGE PROCESSING

Abstract : Digital image processing deals with the manipulation of digital images through a digital computer. It is a subfield of signal and systems but focus particularly on images. DIP focuses on developing a computer system that is able to perform processing on an image. The input of that system is a digital image and the system process that image using efficient algorithms and gives an image as an output. the most common example is adobe photoshop. it is one of the widely used application for processing digital images. Digital imaging is the creation of digital images, such as of a physical scene or of the interior structure of an object. The term is often assumed to imply or include the processing, compression, storage, printing, and display of such images. In digital imaging, the total value of each pixel is represented in binary code. The binary digits for each pixel are called "bits," which are read by the computer to determine the analog display of the image. The number of pixels-per-inch (PPI) is a good indicator of the resolution, which is the ability to distinguish the spatial detail of the digital image.

 EXISTING SYSTEM :

 The Existing System using fuzzy C-means-based clustering algorithm is employed to extract candidate regions of fire from all of the movement-containing regions. In the third stage, a gray level co-occurrence matrix is used to extract texture parameters by tracking red-colored objects in the candidate regions. These texture features are, subsequently, used as inputs of a back-propagation neural network to distinguish between fire and non-fire Detect Output Fire Image.

 DISADVANTAGE :

 • Low Accuracy • High Losses • Memory Size High • Cost High • Processing Time High

 PROPOSED SYSTEM :

 The system has been designed to detect fire in class A and class C objects, as defined in the National Fire Protection Association Standard. Class A objects are defined as being wood, paper, cloth, rubber or plastic. Class C objects are electrical objects such as outlets, power boards, electric motors and so on. Class A and class C have similar fire flame characteristics. This system acquires video input. The system will trigger an audible alarm and provide visual images of the fire as a red box superimposed over the image of the fire flame in the video sequences.

 ADVANTAGE :

 In order to facilitate earlier detection of fire, and to monitor the spread of the fire, we propose a fire detection system based on light detection, as distinct from smoke or heat detection.