On the Evaluation of Handwritten Text Line Detection Algorithms

Even if numerous text line detection algorithms have been proposed, the algorithms are usually compared on a single database and according to a single metric. In this paper, we study the performance of four different text line detection algorithms, on four databases containing very different documents, and according to three metrics (Zone Map, ICDAR and recognition error rate). Our goal is to provide a more comprehensive empirical evaluation of handwritten text line detection methods and to identify what are the key points in the evaluation. We show that the different algorithms yield very different results depending on the type of documents and that two of them are constantly better than the others. We also show that the Zone Map and the ICDAR metric are strongly correlated, but the Zone Map metric provides greater detail on the error types. Finally we show that the geometric metrics are correlated to the recognition error rate on easy to segment databases, but this has to be confirmed on difficult documents.