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EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING CONCEPT:

          The system would indicate to the driver the presence of a sign in advance, so that some incorrect human decisions could be avoided. Two techniques to find the minimum in the energy function are shown: simulated annealing and genetic algorithms. Some problems are addressed, such as uncontrolled lighting conditions; occlusions; and variations in shape, size, and color.

PROPOSED CONCEPT:

          we propose a novel graph based traffic sign detection approach that consists of a saliency measure stage, a graph-based ranking stage, and a multithreshold segmentation stage. Because the graph-based ranking algorithm with specified color and saliency combines the information of color, saliency, spatial, and contextual relationship of nodes, it is more discriminative and robust than the other systems in terms of handling various illumination conditions and shape rotations.

EXISTING  TECHNIQUE :

          ADVANCE DRIVER-ASSISTANCE SYSTEMS (ADASS)

PROPOSED ALGORITHM:

          GRAPH-BASED RANKING AND SEGMENTATION ALGORITHMS

TECHNIQUE DEFINITION:

          ADAS with the automatic ability to extract and identify these signs would help human drivers a great deal, making the navigation task easier and allowing him or her to concentrate on driving the vehicle.

ALGORITHM DEFINITION:

          This graph to represent an image. We then propose a ranking algorithm to exploit the intrinsic manifold structure of the nodes of the graph, and give each node a ranking score according to its saliency, coherence, and similarity with the specified colors. Finally, we propose a multithreshold segmentation approach to segment traffic sign candidate regions.

DRAWBACKS:

          This system is less immune to drastic light changes, occlusions, and object’s deformation.

          The iconographic information, expresses information about exits, city directions, and kilometers, etc., has not been analyzed.

          It  has been not done to analyze a sequence instead of one image at a time.

ADVANTAGES:

          The proposed traffic sign detection approach attained higher F-measure rates than the traditional systems making use of shape information.

          The proposed traffic sign detection approach attained the higher F-measure rates than the traditional systems making use of color information.

          The proposed traffic sign detection approach attained higher F-measure rates than the traditional systems making use of local stability of traffic sign regions and the sliding window paradigm.