diff --git a/turbidity/main.go b/turbidity/main.go
index e1b3034a..f43f375f 100644
--- a/turbidity/main.go
+++ b/turbidity/main.go
@@ -14,17 +14,14 @@ import (
 )
 
 const (
-	nImages  = 6
+	nImages  = 13
 	nSamples = 10
 )
 
 func main() {
-	nImages := 6
-	nSamples := 10
-
 	// Load template and standard image.
 	template := gocv.IMRead("template.jpg", gocv.IMReadGrayScale)
-	standard := gocv.IMRead("standard.jpg", gocv.IMReadGrayScale)
+	standard := gocv.IMRead("default.jpg", gocv.IMReadGrayScale)
 
 	imgs := make([][]gocv.Mat, nImages)
 
@@ -40,7 +37,7 @@ func main() {
 	ts := TurbiditySensor{template: template, standard: standard, k1: 90, k2: 90, scale: 5.0, alpha: 1.0}
 
 	var finalRes Results
-	finalRes.New(nImages)
+	finalRes.new(nImages)
 
 	// Score each image by calculating the average score from camera burst.
 	for i := range imgs {
@@ -52,7 +49,7 @@ func main() {
 		}
 
 		// Add the average result from camera burst.
-		finalRes.Update(average(sample_result.saturation), average(sample_result.contrast), float64(i*10), i)
+		finalRes.update(average(sample_result.saturation), average(sample_result.contrast), float64(i*10), i)
 	}
 
 	// Plot the final results.
@@ -91,7 +88,6 @@ func normalize(slice []float64) []float64 {
 	for i := range slice {
 		out[i] = (slice[i] - min) / (max - min)
 	}
-
 	return out
 }
 
@@ -103,7 +99,6 @@ func average(slice []float64) float64 {
 	for i := range slice {
 		out += slice[i]
 	}
-
 	return out / float64(len(slice))
 }
 
@@ -120,11 +115,9 @@ func plotResults(x, saturation, contrast []float64) error {
 			)
 		},
 	)
-
 	if err != nil {
 		return fmt.Errorf("Could not plot results: %w", err)
 	}
-
 	return nil
 }
 
diff --git a/turbidity/results.go b/turbidity/results.go
index b75dc9ff..4dc24b52 100644
--- a/turbidity/results.go
+++ b/turbidity/results.go
@@ -7,14 +7,14 @@ type Results struct {
 	contrast   []float64
 }
 
-func (r *Results) New(n int) {
+func (r *Results) new(n int) {
 	r.turbidity = make([]float64, n)
 	r.saturation = make([]float64, n)
 	r.contrast = make([]float64, n)
 }
 
 // Update results to add new values at specified index.
-func (r *Results) Update(saturation, contrast, turbidity float64, index int) {
+func (r *Results) update(saturation, contrast, turbidity float64, index int) {
 	r.saturation[index] = saturation
 	r.contrast[index] = contrast
 	r.turbidity[index] = turbidity
diff --git a/turbidity/turbidity.go b/turbidity/turbidity.go
index afef3849..e7708aad 100644
--- a/turbidity/turbidity.go
+++ b/turbidity/turbidity.go
@@ -20,7 +20,7 @@ type TurbiditySensor struct {
 func (ts TurbiditySensor) Evaluate(imgs []gocv.Mat) (Results, error) {
 
 	var result Results
-	result.New(len(imgs))
+	result.new(len(imgs))
 
 	for i := range imgs {
 
@@ -33,13 +33,16 @@ func (ts TurbiditySensor) Evaluate(imgs []gocv.Mat) (Results, error) {
 		// Apply sobel filter.
 		edge := ts.Sobel(marker, ts.scale)
 
+		gocv.IMWrite("marker.jpg", marker)
+		gocv.IMWrite("edge.jpg", edge)
+
 		// Evaluate image.
 		out, err := ts.EvaluateImage(marker, edge, ts.k1, ts.k2, ts.alpha)
 		if err != nil {
 			return result, err
 		}
 
-		result.Update(out[0], out[1], float64(i*10), i)
+		result.update(out[0], out[1], float64(i*10), i)
 	}
 
 	return result, nil
@@ -48,7 +51,6 @@ func (ts TurbiditySensor) Evaluate(imgs []gocv.Mat) (Results, error) {
 // Evaluate image sharpness and contrast using blocks of size k1 by k2. Return a slice of the respective scores.
 func (ts TurbiditySensor) EvaluateImage(img, edge gocv.Mat, k1, k2 int, alpha float64) ([]float64, error) {
 
-	// Slice to store results.
 	result := make([]float64, 2) // [0.0, 0.0]
 
 	if img.Rows()%k1 != 0 || img.Cols()%k2 != 0 {
@@ -127,9 +129,9 @@ func (ts TurbiditySensor) Transform(img gocv.Mat) (gocv.Mat, error) {
 	corners_template := gocv.NewMat()
 
 	// Find corners in image.
-	if !gocv.FindChessboardCorners(img, image.Pt(3, 3), &corners_img, gocv.CalibCBNormalizeImage) {
+	if !gocv.FindChessboardCorners(ts.standard, image.Pt(3, 3), &corners_img, gocv.CalibCBNormalizeImage) {
 		// Apply default if transformation fails.
-		// fmt.Println("Corner detection failed applying standard transformation")
+		fmt.Println("Corner detection failed applying standard transformation")
 		if !gocv.FindChessboardCorners(ts.standard, image.Pt(3, 3), &corners_img, gocv.CalibCBNormalizeImage) {
 			return out, errors.New("Could not find corners in default image")
 		}