Progress in camera-based document image analysis

Doermann, David; Liang, Junbin; Li, Huiping

doi:10.1109/icdar.2003.1227735

Cited by 142 publications

(67 citation statements)

References 34 publications

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“…In order to deal with camera captured images, various kind of problems including perspective distortion, uneven lighting and focusing should be solved [4,5]. We are concerned here with the problem of perspective distortion.…”

Section: Introductionmentioning

confidence: 99%

Use of Affine Invariants in Locally Likely Arrangement Hashing for Camera-Based Document Image Retrieval

Nakai

Kise

Iwamura

2006

Document Analysis Systems VII

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Abstract. 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 Ç´AEµ time where AE 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.

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Section: Introductionmentioning

confidence: 99%

Use of Affine Invariants in Locally Likely Arrangement Hashing for Camera-Based Document Image Retrieval

Nakai

Kise

Iwamura

2006

Document Analysis Systems VII

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“…Today, high definition cameras have made an easy and convenient access to digital images and videos [1]. Recognizing human face using face recognition techniques has become an important research area for computer vision scientists.…”

Section: Introductionmentioning

confidence: 99%

Face recognition system based on principal components analysis and distance measures

Goyal¹,

Meenpal²

2018

IJET

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Face recognition plays a vital role and has a huge scope in the field of biometrics, image processing, artificial intelligence, pattern recognition and computer vision. This paper presents an approach to perform face recognition using Principal Components Analysis (PCA) as feature extraction technique and different distance measures as matching techniques. The proposed method is developed after the deep study of a number of face recognition methods and their outcomes. In the proposed method, Principal Components Analysis is used for facial features extraction and data representation. It generates eigenvalues of the facial images, hence, reduces the dimensionality. The recognition is produced using three different matching techniques (Euclidean, Manhattan and Mahalanobis) and the results are` presented. Yale and Aberdeen Face Databases are used to test and analyze the results of the proposed method.

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“…Numbers of algorithms [1][2][3][4][5][6] are available for this purpose, and many commercial OCR systems [7,8] are now available in the market but most of these systems can recognize only text images having straight text-lines (horizontal) and designed only for a specific script or language. On the other hand, there are few limitations in regard to the source materials and character formatting which make feature extraction and recognition difficult.…”

Section: Introductionmentioning

confidence: 99%

A novel method for straightening curved text-lines in stylistic documents

2014

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Stylistic text can be found on sign boards, street and organizations boards and logos, bulletin boards, announcements, advertisements, dangerous goods plates, warning notices, etc. In stylistic text images, text-lines within an image may have different orientations such as curved in shape or not be parallel to each other. As a result, extraction and subsequent recognition of individual text-lines and words in such images is a difficult task. In this paper, we propose a novel scheme for straightening of curved text-lines using the concept of dilation, flood-fill, robust thinning, and B-spline curve-based fitting. In the proposed scheme, at first, dilation is applied on individual text-lines to cover the area within a certain boundary. Next, thinning is applied to get the path of the text, approximate the path using the B-spline, find the angle between the normal at a point on the curve and the vertical line, and finally visit each point on the text and rotate by their corresponding angles. The proposed methodology is tested on variety of text images containing text-lines in Devanagari, English, and Chinese scripts which is evaluated on the basis of visual perception and the mean square error (MSE) calculation. MSE is calculated by line fitting applied on input and output images. On the basis of evaluation results obtained in our experiments, the proposed method is promising.

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Progress in camera-based document image analysis

Cited by 142 publications

References 34 publications

Use of Affine Invariants in Locally Likely Arrangement Hashing for Camera-Based Document Image Retrieval

Use of Affine Invariants in Locally Likely Arrangement Hashing for Camera-Based Document Image Retrieval

Face recognition system based on principal components analysis and distance measures

A novel method for straightening curved text-lines in stylistic documents

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