"Robust Text Detection in Natural Images with Edge-Enhanced Maximally Stable Extremal Regions." Image Processing (ICIP), 2011 18th IEEE International Conference on. Note that without further enhancements this example can produce reasonable results for a variety of other images, for example, posters.jpg or licensePlates.jpg. This example code is a good starting point for developing more robust text detection algorithms.
#Jpg text recognition software how to
This example showed you how to detect text in an image using the MSER feature detector to first find candidate text regions, and then it described how to use geometric measurements to remove all the non-text regions. This makes the bounding boxes of neighboring text regions overlap such that text regions that are part of the same word or text line form a chain of overlapping bounding boxes. To find neighboring regions, expand the bounding boxes computed earlier with regionprops. One approach for merging individual text regions into words or text lines is to first find neighboring text regions and then form a bounding box around these regions. the set of individual characters, where the meaning of the word is lost without the correct ordering. For example, recognizing the string 'EXIT' vs. This enables recognition of the actual words in an image, which carry more meaningful information than just the individual characters. To use these results for recognition tasks, such as OCR, the individual text characters must be merged into words or text lines. Step 4: Merge Text Regions For Final Detection ResultĪt this point, all the detection results are composed of individual text characters.
0 kommentar(er)
