Local binary pattern on halftone image

This paper presents an efficient and effective way on computing the Local Binary Pattern (LBP) feature from the halftone image for the image retrieval and classification tasks. The Ordered Dither Block Truncation Coding (ODBTC) compresses an image into two new representations, i.e. color quantizer and halftone image. Two image features can be generated from these two new representations for computing similarity degree between several images in the image retrieval and classification processes. Color Histogram Feature (CHF) can be easily computed from color quantizer, whereas the Block-based Local Binary Pattern (BLBP) can be directly applied on halftone image. The feature extraction process avoids the ODBTC decoding step making it very useful in real time application requiring fast feature computation. As documented in the experimental result, the proposed method offers a promising result on the image classification and retrieval tasks compared to that of the former schemes.

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