IPSILON: Incremental Parsing for Semantic Indexing of Latent Concepts

Abstract

A new framework for content-based image retrieval, which takes advantage of the source characterization property of a universal source coding scheme, is investigated. Based upon a new class of multidimensional incremental parsing algorithm, extended from the Lempel-Ziv incremental parsing code, the proposed method captures the occurrence pattern of visual elements from a given image. A linguistic processing technique, namely the latent semantic analysis (LSA) method, is then employed to identify associative ensembles of visual elements, which lay the foundation for intelligent visual information analysis. In 2-D applications, incremental parsing decomposes an image into elementary patches that are different from the conventional fixed square-block type patches. When used in compressive representations, it is amenable in schemes that do not rely on average distortion criteria, a methodology that is a departure from the conventional vector quantization. We call this methodology a parsed representation. In this article, we present our implementations of an image retrieval system, called IPSILON, with parsed representations induced by different perceptual distortion thresholds. We evaluate the effectiveness of the use of the parsed representations by comparing their performance with that of four image retrieval systems, one using the conventional vector quantization for visual information analysis under the same LSA paradigm, another using a method called SIMPLIcity which is based upon an image segmentation and integrated region matching, and the other two based upon query-by-semantic-example and query-by-visual-example. The first two of them were tested with 20,000 images of natural scenes, and the others were tested with a portion of the images. The experimental results show that the proposed parsed representation efficiently captures the salient features in visual images and the IPSILON systems outperform other systems in terms of retrieval precision and distortion robustness.

Multidimensional Incremental Parsing: Current Status and Future Directions

“…To prevent running into known issue of suffix ambiguity, suffixing order must be defined. In this paper, we use the same suffixing order used in [5]. Let be the original codeword, and let be its size vector.…”

“…A binary decimation field is defined as 0 if and 1 otherwise. Also (5) The decimation level is basically indicating the number of symbols that can be encoded by a given match and were not encoded already by a previous match. This scheme obviously allows match overlap, yet it could be desirable to minimize such overlap.…”

“…In incremental parsing coders such as LZ78 [1], and its multidimensional variant MDIP threshold [2]- [5], no prior knowledge of the source and its statistical descriptors is assumed. This is particularly useful in data streaming applications, where the source itself is altogether unavailable in its entirety while coding.…”

Bag-of-Words Representation in Image Annotation: A Review

“…Bae and Juang [79] apply the idea of linguistic parsing to generate the BoW feature for image annotation. That is, images are represented by a number of variable-size patches by a multidimensional incremental parsing algorithm.…”