Use of Affine Invariants in Locally Likely Arrangement Hashing for Camera-Based Document Image Retrieval
نویسندگان
چکیده
Camera-based document image retrieval is a task of searching document images from the database based on query images captured using digital cameras. For this task, it is required to solve the problem of “perspective distortion” of images, as well as to establish a way of matching document images efficiently. To solve these problems we have proposed a method called Locally Likely Arrangement Hashing (LLAH) which is characterized by both the use of a perspective invariant to cope with the distortion and the efficiency: LLAH only requires O(N) time where N is the number of feature points that describe the query image. In this paper, we introduce into LLAH an affine invariant instead of the perspective invariant so as to improve its adjustability. Experimental results show that the use of the affine invariant enables us to improve either the accuracy from 96.2% to 97.8%, or the retrieval time from 112 msec./query to 75 msec./query by selecting parameters of processing.
منابع مشابه
A multi-layer separation based system for camera-based complex map image retrieval
In this paper, we present a method of camera-based document image retrieval for heterogeneous-content document using a multi-layer separating approach. We use Locally Likely Arrangement Hashing (LLAH) extracting text features on the layer which contains text. In addition, we employ a technique of reducing the memory required for storing the hash table. Experiment result show that our approach i...
متن کاملCamera Based Document Image Retrieval with More Time and Memory Efficient LLAH
In this paper, we propose improvements of our camerabased document image retrieval method with Locally Likely Arrangement Hashing (LLAH). While LLAH has high accuracy, efficiency and robustness, it requires a large amount of memory. It is also required to speed up the retrieval of LLAH for applications to real-time document image retrieval. For these purposes, we introduce the following two imp...
متن کاملRecovery and localization of handwritings by a camera-pen based on tracking and document image retrieval
We propose a camera-based method for digital recovery of handwritings on ordinary paper. Our method is characterized by the following two points: (1) it requires no special device such as special paper other than a camera-pen to recover handwritings, (2) if the handwriting is on a printed document, the method is capable of localizing it onto an electronic equivalent of the printed document. The...
متن کاملPosition Detection For a Camera Pen Using LLAH and Dot Patterns
In this report, we present a method of position detection for a low-cost camera-pen. Our method allows reconstruction of handwriting, as well as retrieval of the particular document that is being written onto. For this matter, we use a point pattern printed onto the document’s background, which is indexed using Locally Likely Arrangement Hashing. For position detection, the dot pattern is extra...
متن کاملImprovement of Retrieval Speed and Required Amount of Memory for Geometric Hashing by Combining Local Invariants
The geometric hashing (GH) is a well-known model-based object recognition technique with good properties both in retrieval speed and required amount of memory. However, it has a significant weak point; as the number of objects increases, both retrieval speed and required amount of memory increase in the cubic, fourth or higher order. Recently, a new technique “locally likely arrangement hashing...
متن کامل