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How to detect edges using Canny in Android in low brightness and ignore shadows?
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I'm developing an Android application to perform image segmentation using Opencv in real time.
The problem is when I applied Canny edge detector, there is always gaps in detected contours even in high brightness environment but detection is accurate when I turn on my smartphone flash.
And when I turn on flash, shadows are also detected which isn't good for my purposes.
I tried to enhance pixels values using Opencv method convertTo and I tried also increasing camera exposure, but in vain.
Here is my code
Imgproc.cvtColor(orr, orr, Imgproc.COLOR_RGB2HSV);
Core.split(orr, channels);
orr = channels.get(1);
//orr.convertTo(orr, orr.type(), 1.1);
Core.meanStdDev(orr, mu, stddev);
CLAHE clahe = Imgproc.createCLAHE();
clahe.setClipLimit(1);
clahe.apply(orr, orr);
clahe.collectGarbage();
Imgproc.GaussianBlur(orr, orr, new Size(5, 5), 3);
Imgproc.Canny(orr, orr, mu.get(0, 0)[0], stddev.get(0, 0)[0], 3, false);
Imgproc.morphologyEx(orr, orr, Imgproc.MORPH_CLOSE, kernell);
Imgproc.dilate(orr, orr, Imgproc.getStructuringElement(Imgproc.MORPH_CROSS, new Size(3, 3)));
Imgproc.findContours(orr, contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
for (int i = contours.size() - 1; i >= 0; i--)
if (contours.size() > 0)
MatOfPoint2f approxCurve = new MatOfPoint2f();
rectList.clear();
for (int idx = 0; idx < contours.size(); idx++)
//Convert contours(i) from MatOfPoint to MatOfPoint2f
MatOfPoint2f contour2f = new MatOfPoint2f(contours.get(idx).toArray());
//Processing on mMOP2f1 which is in type MatOfPoint2f
double approxDistance = Imgproc.arcLength(contour2f, true) * 0.02;
Imgproc.approxPolyDP(contour2f, approxCurve, approxDistance, true);
//Convert back to MatOfPoint
MatOfPoint points = new MatOfPoint(approxCurve.toArray());
// Get bounding rect of contour
Rect rectt = Imgproc.boundingRect(points);
rectList.add(rect);
Mat miniature = new Mat(orr, new Rect(rectt.tl(), rectt.br()));
mats.add(miniature);
// draw enclosing rectangle (all same color, but you could use variable i to make them unique)
Imgproc.rectangle(rotated, rectt.tl(), rectt.br(), new Scalar(255, 0, 0));
Imgproc.resize(rotated, rotated, new Size(rotated.width() * 2, rotated.height() * 2));
long e2 = Core.getTickCount();
long e = e2 - e1;
double time = e / Core.getTickFrequency();
Here is the image without flash
And here is the output result with flash
So my question is what can I do to have accurate detection without using phone flash ?
android image-processing computer-vision opencv4android canny-operator asked Mar 25 at 9:42
AmineAmine
1,0701 gold badge4 silver badges15 bronze badges
add a comment |
I'm developing an Android application to perform image segmentation using Opencv in real time.
The problem is when I applied Canny edge detector, there is always gaps in detected contours even in high brightness environment but detection is accurate when I turn on my smartphone flash.
And when I turn on flash, shadows are also detected which isn't good for my purposes.
I tried to enhance pixels values using Opencv method convertTo and I tried also increasing camera exposure, but in vain.
Here is my code
Imgproc.cvtColor(orr, orr, Imgproc.COLOR_RGB2HSV);
Core.split(orr, channels);
orr = channels.get(1);
//orr.convertTo(orr, orr.type(), 1.1);
Core.meanStdDev(orr, mu, stddev);
CLAHE clahe = Imgproc.createCLAHE();
clahe.setClipLimit(1);
clahe.apply(orr, orr);
clahe.collectGarbage();
Imgproc.GaussianBlur(orr, orr, new Size(5, 5), 3);
Imgproc.Canny(orr, orr, mu.get(0, 0)[0], stddev.get(0, 0)[0], 3, false);
Imgproc.morphologyEx(orr, orr, Imgproc.MORPH_CLOSE, kernell);
Imgproc.dilate(orr, orr, Imgproc.getStructuringElement(Imgproc.MORPH_CROSS, new Size(3, 3)));
Imgproc.findContours(orr, contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
for (int i = contours.size() - 1; i >= 0; i--)
if (contours.size() > 0)
MatOfPoint2f approxCurve = new MatOfPoint2f();
rectList.clear();
for (int idx = 0; idx < contours.size(); idx++)
//Convert contours(i) from MatOfPoint to MatOfPoint2f
MatOfPoint2f contour2f = new MatOfPoint2f(contours.get(idx).toArray());
//Processing on mMOP2f1 which is in type MatOfPoint2f
double approxDistance = Imgproc.arcLength(contour2f, true) * 0.02;
Imgproc.approxPolyDP(contour2f, approxCurve, approxDistance, true);
//Convert back to MatOfPoint
MatOfPoint points = new MatOfPoint(approxCurve.toArray());
// Get bounding rect of contour
Rect rectt = Imgproc.boundingRect(points);
rectList.add(rect);
Mat miniature = new Mat(orr, new Rect(rectt.tl(), rectt.br()));
mats.add(miniature);
// draw enclosing rectangle (all same color, but you could use variable i to make them unique)
Imgproc.rectangle(rotated, rectt.tl(), rectt.br(), new Scalar(255, 0, 0));
Imgproc.resize(rotated, rotated, new Size(rotated.width() * 2, rotated.height() * 2));
long e2 = Core.getTickCount();
long e = e2 - e1;
double time = e / Core.getTickFrequency();
Here is the image without flash
And here is the output result with flash
So my question is what can I do to have accurate detection without using phone flash ?
android image-processing computer-vision opencv4android canny-operator asked Mar 25 at 9:42
AmineAmine
1,0701 gold badge4 silver badges15 bronze badges
Have you tried reducingthreshold1andthreshold2?
– greeble31
Mar 25 at 22:04
Threshold is auto calculated using mean .
– Amine
Mar 25 at 23:12
I hear you, but the threshold calculated is not suitable for your purposes. I think you've just demonstrated that. Threshold should be regarded as a tunable parameter, here. After all, you're not using AI; you're using Canny.
– greeble31
Mar 25 at 23:23
Thank you Sir, but i need it to be generic for most cases, so when I use low threshold, detection is bright places won't work
– Amine
Mar 26 at 1:14
add a comment |
I'm developing an Android application to perform image segmentation using Opencv in real time.
The problem is when I applied Canny edge detector, there is always gaps in detected contours even in high brightness environment but detection is accurate when I turn on my smartphone flash.
And when I turn on flash, shadows are also detected which isn't good for my purposes.
I tried to enhance pixels values using Opencv method convertTo and I tried also increasing camera exposure, but in vain.
Here is my code
Imgproc.cvtColor(orr, orr, Imgproc.COLOR_RGB2HSV);
Core.split(orr, channels);
orr = channels.get(1);
//orr.convertTo(orr, orr.type(), 1.1);
Core.meanStdDev(orr, mu, stddev);
CLAHE clahe = Imgproc.createCLAHE();
clahe.setClipLimit(1);
clahe.apply(orr, orr);
clahe.collectGarbage();
Imgproc.GaussianBlur(orr, orr, new Size(5, 5), 3);
Imgproc.Canny(orr, orr, mu.get(0, 0)[0], stddev.get(0, 0)[0], 3, false);
Imgproc.morphologyEx(orr, orr, Imgproc.MORPH_CLOSE, kernell);
Imgproc.dilate(orr, orr, Imgproc.getStructuringElement(Imgproc.MORPH_CROSS, new Size(3, 3)));
Imgproc.findContours(orr, contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
for (int i = contours.size() - 1; i >= 0; i--)
if (contours.size() > 0)
MatOfPoint2f approxCurve = new MatOfPoint2f();
rectList.clear();
for (int idx = 0; idx < contours.size(); idx++)
//Convert contours(i) from MatOfPoint to MatOfPoint2f
MatOfPoint2f contour2f = new MatOfPoint2f(contours.get(idx).toArray());
//Processing on mMOP2f1 which is in type MatOfPoint2f
double approxDistance = Imgproc.arcLength(contour2f, true) * 0.02;
Imgproc.approxPolyDP(contour2f, approxCurve, approxDistance, true);
//Convert back to MatOfPoint
MatOfPoint points = new MatOfPoint(approxCurve.toArray());
// Get bounding rect of contour
Rect rectt = Imgproc.boundingRect(points);
rectList.add(rect);
Mat miniature = new Mat(orr, new Rect(rectt.tl(), rectt.br()));
mats.add(miniature);
// draw enclosing rectangle (all same color, but you could use variable i to make them unique)
Imgproc.rectangle(rotated, rectt.tl(), rectt.br(), new Scalar(255, 0, 0));
Imgproc.resize(rotated, rotated, new Size(rotated.width() * 2, rotated.height() * 2));
long e2 = Core.getTickCount();
long e = e2 - e1;
double time = e / Core.getTickFrequency();
Here is the image without flash
And here is the output result with flash
So my question is what can I do to have accurate detection without using phone flash ?
android image-processing computer-vision opencv4android canny-operator asked Mar 25 at 9:42
AmineAmine
1,0701 gold badge4 silver badges15 bronze badges
I'm developing an Android application to perform image segmentation using Opencv in real time.
The problem is when I applied Canny edge detector, there is always gaps in detected contours even in high brightness environment but detection is accurate when I turn on my smartphone flash.
And when I turn on flash, shadows are also detected which isn't good for my purposes.
I tried to enhance pixels values using Opencv method convertTo and I tried also increasing camera exposure, but in vain.
Here is my code
Imgproc.cvtColor(orr, orr, Imgproc.COLOR_RGB2HSV);
Core.split(orr, channels);
orr = channels.get(1);
//orr.convertTo(orr, orr.type(), 1.1);
Core.meanStdDev(orr, mu, stddev);
CLAHE clahe = Imgproc.createCLAHE();
clahe.setClipLimit(1);
clahe.apply(orr, orr);
clahe.collectGarbage();
Imgproc.GaussianBlur(orr, orr, new Size(5, 5), 3);
Imgproc.Canny(orr, orr, mu.get(0, 0)[0], stddev.get(0, 0)[0], 3, false);
Imgproc.morphologyEx(orr, orr, Imgproc.MORPH_CLOSE, kernell);
Imgproc.dilate(orr, orr, Imgproc.getStructuringElement(Imgproc.MORPH_CROSS, new Size(3, 3)));
Imgproc.findContours(orr, contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
for (int i = contours.size() - 1; i >= 0; i--)
if (contours.size() > 0)
MatOfPoint2f approxCurve = new MatOfPoint2f();
rectList.clear();
for (int idx = 0; idx < contours.size(); idx++)
//Convert contours(i) from MatOfPoint to MatOfPoint2f
MatOfPoint2f contour2f = new MatOfPoint2f(contours.get(idx).toArray());
//Processing on mMOP2f1 which is in type MatOfPoint2f
double approxDistance = Imgproc.arcLength(contour2f, true) * 0.02;
Imgproc.approxPolyDP(contour2f, approxCurve, approxDistance, true);
//Convert back to MatOfPoint
MatOfPoint points = new MatOfPoint(approxCurve.toArray());
// Get bounding rect of contour
Rect rectt = Imgproc.boundingRect(points);
rectList.add(rect);
Mat miniature = new Mat(orr, new Rect(rectt.tl(), rectt.br()));
mats.add(miniature);
// draw enclosing rectangle (all same color, but you could use variable i to make them unique)
Imgproc.rectangle(rotated, rectt.tl(), rectt.br(), new Scalar(255, 0, 0));
Imgproc.resize(rotated, rotated, new Size(rotated.width() * 2, rotated.height() * 2));
long e2 = Core.getTickCount();
long e = e2 - e1;
double time = e / Core.getTickFrequency();
Here is the image without flash
And here is the output result with flash
So my question is what can I do to have accurate detection without using phone flash ?
android image-processing computer-vision opencv4android canny-operator android image-processing computer-vision opencv4android canny-operator asked Mar 25 at 9:42
AmineAmine
1,0701 gold badge4 silver badges15 bronze badges
asked Mar 25 at 9:42
AmineAmine
1,0701 gold badge4 silver badges15 bronze badges
asked Mar 25 at 9:42
AmineAmine
1,0701 gold badge4 silver badges15 bronze badges
asked Mar 25 at 9:42
AmineAmine
1,0701 gold badge4 silver badges15 bronze badges
asked Mar 25 at 9:42
AmineAmine
1,0701 gold badge4 silver badges15 bronze badges
1,0701 gold badge4 silver badges15 bronze badges
Have you tried reducingthreshold1andthreshold2?
– greeble31
Mar 25 at 22:04
Threshold is auto calculated using mean .
– Amine
Mar 25 at 23:12
I hear you, but the threshold calculated is not suitable for your purposes. I think you've just demonstrated that. Threshold should be regarded as a tunable parameter, here. After all, you're not using AI; you're using Canny.
– greeble31
Mar 25 at 23:23
Thank you Sir, but i need it to be generic for most cases, so when I use low threshold, detection is bright places won't work
– Amine
Mar 26 at 1:14
add a comment |
Have you tried reducingthreshold1andthreshold2?
– greeble31
Mar 25 at 22:04
Threshold is auto calculated using mean .
– Amine
Mar 25 at 23:12
I hear you, but the threshold calculated is not suitable for your purposes. I think you've just demonstrated that. Threshold should be regarded as a tunable parameter, here. After all, you're not using AI; you're using Canny.
– greeble31
Mar 25 at 23:23
Thank you Sir, but i need it to be generic for most cases, so when I use low threshold, detection is bright places won't work
– Amine
Mar 26 at 1:14
Have you tried reducing
threshold1 and threshold2?– greeble31
Mar 25 at 22:04
Have you tried reducing
threshold1 and threshold2?– greeble31
Mar 25 at 22:04
Threshold is auto calculated using mean .
– Amine
Mar 25 at 23:12
Threshold is auto calculated using mean .
– Amine
Mar 25 at 23:12
I hear you, but the threshold calculated is not suitable for your purposes. I think you've just demonstrated that. Threshold should be regarded as a tunable parameter, here. After all, you're not using AI; you're using Canny.
– greeble31
Mar 25 at 23:23
I hear you, but the threshold calculated is not suitable for your purposes. I think you've just demonstrated that. Threshold should be regarded as a tunable parameter, here. After all, you're not using AI; you're using Canny.
– greeble31
Mar 25 at 23:23
Thank you Sir, but i need it to be generic for most cases, so when I use low threshold, detection is bright places won't work
– Amine
Mar 26 at 1:14
Thank you Sir, but i need it to be generic for most cases, so when I use low threshold, detection is bright places won't work
– Amine
Mar 26 at 1:14
add a comment |
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Have you tried reducing
threshold1andthreshold2?– greeble31
Mar 25 at 22:04
Threshold is auto calculated using mean .
– Amine
Mar 25 at 23:12
I hear you, but the threshold calculated is not suitable for your purposes. I think you've just demonstrated that. Threshold should be regarded as a tunable parameter, here. After all, you're not using AI; you're using Canny.
– greeble31
Mar 25 at 23:23
Thank you Sir, but i need it to be generic for most cases, so when I use low threshold, detection is bright places won't work
– Amine
Mar 26 at 1:14