18-03-2011, 02:24 PM
Amalant Alfias.A
Abirami.T
[attachment=10494]
AN ELECTRONIC EYE FOR VISUALLY IMPAIRED
Abstract: This paper proposes a method for detecting frontal pedestrian crossings from image data obtained with a single camera as a travel aid for the visually challenged. The process of detecting a crossing is a pre-process followed by the process for detecting the state of the traffic lights. It is important for the visually challenged to know whether or not a frontal area is a crossing. The existence of a crossing is detected in two steps. In the first step, edge detection and pattern detection are employed to identify the crossing. In the second step, the existence of a crossing is detected by checking the periodicity of white lines on the road using projective invariants.
I) INTRODUCTION
Blindness is the most feared of all human ailments. Crossing busy roads can be a challenge for people with good vision. For blind people, it is a perilous activity. Our electronic eye aims at helping millions of blind and visually impaired people lead more independent lives.
The electronic eye can be adapted to help the blind or visually impaired get around without a walking stick or seeing-eye dog. Canes and other travel aids with sonar or lasers can alert the user to approaching objects. Global Positioning Systems can tell what streets, restaurants, parks and other landmarks the user is passing. Devices like these are very good at giving locations and directions. But the limitations of G.P.S. technology mean that they cannot pin down the location of a curb or crosswalk and frequently fail in areas that have many tall buildings and high traffic. None of these devices are able to specifically identify a crosswalk, nor do they have the potential for figuring out the state of the traffic signals.
An effective navigation system would improve the mobility of millions of blind people all over the world. Our new “eye” will allow blind people to cross busy roads in total safety for the first time. Our “electronic eye”, which would be mounted on a pair of glasses, will be capable of detecting the existence and location of a pedestrian crossing, and at the same time measure the width of the road to the nearest step and detect the color of the traffic lights.
II) AN OVERVIEW OF OUR ELECTRONIC EYE
We have developed a system that is able to detect the existence of a pedestrian crossing in front of a blind person using a single camera. By measuring the width of the road and the color of traffic lights, this single camera can now give the blind all the information they need to cross a road in safety. The camera would be mounted at eye level, and be connected to a tiny computer. It will relay information using a voice speech system and give vocal commands and information through a small speaker placed near the ear.
III) FUNCTIONING OF THE SYSTEM
1) Tells the user whether any cross road is present
2) Tells the user whether the traffic signal is favorable or not
3) Tells the user the time taken to cross the road.
The style of crosswalks commonly used in India are known as zebra crossings and they feature a series of thick white bands that run in the same direction as the vehicle traffic.
To detect the presence of a zebra crossing we use the “projective invariant” which takes the distance between the white lines and a set of linear points on the edges of the white lines. This gives an accurate way of detecting whether crossing is present in a given image or not.
The length of a pedestrian crossing is measured by projective geometry. The camera makes an image of the white lines painted on the road, and then the actual distances are determined using the properties of geometric shapes as seen in the image.
The traffic light detector checks images for symmetrical shapes and compares them to a list of road signs. If the pedestrian light is ON, the voice speech system instructs the user to cross the road.
The timer unit calculates the average time required by the visually challenged person to cross the road and ‘tells’ it to the user via the voice speech system.
High-level scene interpretation applied to the processed images will produce a symbolic description of the scene. The symbolic description is then converted into verbal instructions appropriate to the needs of the user by using voice speech software
IV) IMAGE ANALYSER
The image analyzer contains the bitmap image, which has to be processed to detect the presence of a zebra crossing. Given an X-bit per pixel image, slicing the image at different planes (bit-planes) plays an important role in image processing.
Edge detection :
One way to detect edges or variations within a region of an image is by using the gradient operator. There are several well-known gradient filters. In this experiment we use the Sobel gradients, which are obtained by convolving the image with two kernels, one for each direction.
Crossroad pattern detection:
The zebra crossing has alternate white bands running across the width of the road. This pattern has to be recognized to confirm the presence of a crossing. To detect basic shapes within the image, we make use of the Hough transform. At its simplest the Hough transform can be used to detect straight lines from edges detected in an earlier processing step.
If the pixels detected fall on a straight line then they can be expressed by the equation:
Y=mx+c
The basis of the Hough transform is to translate the points in (x, y) space into (m,c) space using the equation:
c=(-x)m+y
Thus each point in (x,y) space (i.e. the image) represents a line in (m,c) space. Where three or more of these lines intersect a value can be found for the gradient (m) and intercept © of the line that connects the (x,y) space points.
Calculation of the width of the road and time required to cross it:
Calculation of the width of the road is based on the concept of projection invariants. This requires us to define the term Cross Ratio.
Abirami.T
[attachment=10494]
AN ELECTRONIC EYE FOR VISUALLY IMPAIRED
Abstract: This paper proposes a method for detecting frontal pedestrian crossings from image data obtained with a single camera as a travel aid for the visually challenged. The process of detecting a crossing is a pre-process followed by the process for detecting the state of the traffic lights. It is important for the visually challenged to know whether or not a frontal area is a crossing. The existence of a crossing is detected in two steps. In the first step, edge detection and pattern detection are employed to identify the crossing. In the second step, the existence of a crossing is detected by checking the periodicity of white lines on the road using projective invariants.
I) INTRODUCTION
Blindness is the most feared of all human ailments. Crossing busy roads can be a challenge for people with good vision. For blind people, it is a perilous activity. Our electronic eye aims at helping millions of blind and visually impaired people lead more independent lives.
The electronic eye can be adapted to help the blind or visually impaired get around without a walking stick or seeing-eye dog. Canes and other travel aids with sonar or lasers can alert the user to approaching objects. Global Positioning Systems can tell what streets, restaurants, parks and other landmarks the user is passing. Devices like these are very good at giving locations and directions. But the limitations of G.P.S. technology mean that they cannot pin down the location of a curb or crosswalk and frequently fail in areas that have many tall buildings and high traffic. None of these devices are able to specifically identify a crosswalk, nor do they have the potential for figuring out the state of the traffic signals.
An effective navigation system would improve the mobility of millions of blind people all over the world. Our new “eye” will allow blind people to cross busy roads in total safety for the first time. Our “electronic eye”, which would be mounted on a pair of glasses, will be capable of detecting the existence and location of a pedestrian crossing, and at the same time measure the width of the road to the nearest step and detect the color of the traffic lights.
II) AN OVERVIEW OF OUR ELECTRONIC EYE
We have developed a system that is able to detect the existence of a pedestrian crossing in front of a blind person using a single camera. By measuring the width of the road and the color of traffic lights, this single camera can now give the blind all the information they need to cross a road in safety. The camera would be mounted at eye level, and be connected to a tiny computer. It will relay information using a voice speech system and give vocal commands and information through a small speaker placed near the ear.
III) FUNCTIONING OF THE SYSTEM
1) Tells the user whether any cross road is present
2) Tells the user whether the traffic signal is favorable or not
3) Tells the user the time taken to cross the road.
The style of crosswalks commonly used in India are known as zebra crossings and they feature a series of thick white bands that run in the same direction as the vehicle traffic.
To detect the presence of a zebra crossing we use the “projective invariant” which takes the distance between the white lines and a set of linear points on the edges of the white lines. This gives an accurate way of detecting whether crossing is present in a given image or not.
The length of a pedestrian crossing is measured by projective geometry. The camera makes an image of the white lines painted on the road, and then the actual distances are determined using the properties of geometric shapes as seen in the image.
The traffic light detector checks images for symmetrical shapes and compares them to a list of road signs. If the pedestrian light is ON, the voice speech system instructs the user to cross the road.
The timer unit calculates the average time required by the visually challenged person to cross the road and ‘tells’ it to the user via the voice speech system.
High-level scene interpretation applied to the processed images will produce a symbolic description of the scene. The symbolic description is then converted into verbal instructions appropriate to the needs of the user by using voice speech software
IV) IMAGE ANALYSER
The image analyzer contains the bitmap image, which has to be processed to detect the presence of a zebra crossing. Given an X-bit per pixel image, slicing the image at different planes (bit-planes) plays an important role in image processing.
Edge detection :
One way to detect edges or variations within a region of an image is by using the gradient operator. There are several well-known gradient filters. In this experiment we use the Sobel gradients, which are obtained by convolving the image with two kernels, one for each direction.
Crossroad pattern detection:
The zebra crossing has alternate white bands running across the width of the road. This pattern has to be recognized to confirm the presence of a crossing. To detect basic shapes within the image, we make use of the Hough transform. At its simplest the Hough transform can be used to detect straight lines from edges detected in an earlier processing step.
If the pixels detected fall on a straight line then they can be expressed by the equation:
Y=mx+c
The basis of the Hough transform is to translate the points in (x, y) space into (m,c) space using the equation:
c=(-x)m+y
Thus each point in (x,y) space (i.e. the image) represents a line in (m,c) space. Where three or more of these lines intersect a value can be found for the gradient (m) and intercept © of the line that connects the (x,y) space points.
Calculation of the width of the road and time required to cross it:
Calculation of the width of the road is based on the concept of projection invariants. This requires us to define the term Cross Ratio.
