1. Support vector machine-based text detection in digital video
Pattern Recognition 34 (2001) pp
Received 16 May 2000; accepted 24 May 2000
Kwang In Kim, Keechul Jung, Se Hyun Park, Hang Joon Kim*

2. Problem To detect texts in images Approach Texture analysis
No a priori knowledge
Size, color, arrangements of texts
Text regions can be identified with box or composition of boxes
Approach
Classify the pixel in the image into text or non text
Multi-scaled
Pyramid image
Detecting algorithm is applied to each Pyramid level
Texture analysis
Support vector machine (SVM) as Classifier

3. Proposed Architecture

4. Feature Space
P-degree polynomial kernel function

5. Text Detection Experimental Results
2000 Key frame (640480) manually selected
200 Korean news archives and 200 commercials
Train Samples
500 samples
Test Samples
1500 samples
Detection results (1500 frame)
Just only 86 false detections (too low resolution)
Correction rate 94.3%

6. Experimental Results (cont)