In ImageMagick 6, you can blur the image enough that the text overlaps and threshold so that the text boxes are each one large black region on a white background. Then you can use connected-components to find each separate black gray(0) region and its bounding box. Then crop the original image for each such region using the bounding box values.
Input:
![enter image description here]()
Unix Syntax (adjust the blur to be just large enough to keep the text regions solid black):
infile="image.png"
inname=`convert -ping $infile -format "%t" info:`
OLDIFS=$IFS
IFS=$'\n'
arr=(`convert $infile -blur 0x5 -auto-level -threshold 99% -type bilevel +write tmp.png \
-define connected-components:verbose=true \
-connected-components 8 \
null: | tail -n +2 | sed 's/^[ ]*//'`)
num=${#arr[*]}
IFS=$OLDIFS
for ((i=0; i<num; i++)); do
#echo "${arr[$i]}"
color=`echo ${arr[$i]} | cut -d\ -f5`
bbox=`echo ${arr[$i]} | cut -d\ -f2`
echo "color=$color; bbox=$bbox"
if [ "$color" = "gray(0)" ]; then
convert $infile -crop $bbox +repage -fuzz 10% -trim +repage ${inname}_$i.png
fi
done
Textual Listing:
color=gray(255); bbox=892x1008+0+0
color=gray(0); bbox=337x430+36+13
color=gray(0); bbox=430x337+266+630
color=gray(0); bbox=202x147+506+252
tmp.png showing the blurred and thresholded regions:
![enter image description here]()
Cropped Images:
![enter image description here]()
![enter image description here]()
![enter image description here]()
To seperate the first image, erode, threshold, and findContours, rotate if necessary.Then I get these detections and these cropeds. But the text in the image is too small to do OCR. Your updated image is even worse for image processing. – Eolith