Thesis (PDF) - Signal & Image Processing Lab

100 CHAPTER 6. EXTREMA-WATERSHED TREE EXAMPLE
Method used Recognition result Quality coeff.
Image without noise, without pre-processing 70-587-07 3.75
Noisy image, without pre-processing 20-687-07 3.47
Averaging filter 70-587-02 3.65
Median filter 70-587-07 3.75
Regular open by reconstruct 79-687-07 3.65
Regular quasi dual open by reconstruct 70-587-07 3.79
EWT filter 70-587-07 3.84
Table 6.1: OCR results comparison with different pre-processing methods.
the pre-processing is applied, the quality coefficient increases and correct recognition
is achieved. Sometimes OCR results are even better for pre-processed noisy image,
than for not noisy image.
In order to measure the effectiveness of the proposed approach, a number of other
pre-processing filters were used. A simple averaging filter, using the same structuring
element was used to filter the image. The result is shown in Fig. 6.33. As can be seen
in Table 6.1, this particular pre-processing gives a very poor result. A median filter
with the same structuring element, which is shown in Fig. 6.34, gives better results
than averaging. Opening-by-reconstruction results, using regular gray scale image
morphology, are shown in Fig. 6.35. The image looks much better, although it is
apparent that the filter is not self dual. The OCR, as seen in Table 6.1, successfully
recognizes the plate number and the quality coefficient goes higher. In order to
handle the lack of duality of regular morphology, we took the following approach:
Two opening by reconstruction operations were performed using the scheme shown
in equation 6.4.
Iquasi−self−dual = 256 − OR(256 − OR(Ioriginal)) (6.4)
Where OR is opening by reconstruction operator, 256 is the maximum gray level and
Ioriginal is the input image.
The filter result is shown in Fig. 6.36. The result looks fine but is a bit more
corrupted than the EWT filtering result in Fig. 6.32. The OCR results, shown in
Table 6.1, are slightly worst than the EWT filtering.