Ching Suen

• Concordia University

Reticulocyte count is a routine blood test that can be an essential source of knowledge for medical doctors to diagnose and assess patients’ health condition. In fact, the automation of this blood test will reduce cost and time, in addition to protecting laboratorians’ lives, especially during pandemics and outbreaks. However, human reticulocyte da...

Most of the methods on handwritten recognition in the literature are focused and evaluated on Black and White (BW) image databases. In this paper we try to answer a fundamental question in document recognition. Using Convolutional Neural Networks (CNNs), as eye simulator, we investigate to see whether color modalities of handwritten digits and word...

Peripheral Blood Smear (PBS) analysis is a vital routine test carried out by medical specialists to assess some health aspects of individuals. The automation of blood analysis has attracted the attention of researchers in recent years, as it will not only save time, money and reduce errors, but also protect and save lives of front-line workers, esp...

Most of the methods on handwritten digit recognition in the literature are focused and evaluated on black and white image databases. In this paper we try to answer a fundamental question in document recognition. Using Convolutional Neural Networks (CNNs), we investigate to see whether color modalities of handwritten digits affect their recognition...

In an insurance company, manual underwriting is costly, time consuming, and complex. Simulating underwriters with AI is an absolutely time saving and cost fitting solution. As a result, a Hybrid Multiple Classifier System, combining three classifiers with rejection options: XGBoost, Random Forest, and SVM, was designed and applied on production. An...

Many difficulties are facing a handwritten Arabic recognition system such as unlimited variation in human handwriting, similarities of distinct character shapes, interconnections of neighboring characters and their position in a word. This paper presents a handwritten Arabic character recognition system based on BA algorithm. BA algorithm is adopte...

Although widely used, Multilinear PCA (MPCA), one of the leading multilinear analysis methods, still suffers from four major drawbacks. First, it is very sensitive to outliers and noise. Second, it is unable to cope with missing values. Third, it is computationally expensive since MPCA deals with large multi-dimensional datasets. Finally, it is una...

Electronic reading opens new avenues especially with the advance of modern reading devices. The new generation of Personal Digital Assistants PDAs is more popular and more affordable. Therefore, it is necessary to re-evaluate typefaces used in these devices as they form a substantial component in reading. In this chapter, we present a survey which...

Recently, robust sparse coding achieves high recognition rates on face recognition, even when dealing with occluded images. However, robust sparse coding is known that only guarantee the coefficient is global sparse when solving the sparse coefficient. In this paper, we divided the coefficient vector into multiple regions. Then, we enabled the elem...

Breast cancer is the most common cancer among women in the world. A mammography is a common approach to early cancer detection by radiologists. In the last decade, a new technology as digital tomosynthesis was introduced in the field of breast cancer screening. It produces multiple x-ray images of the breast taken at different angles. These images...

Face recognition is an active topic in recognition systems, while the face occlusion is one of the most challenging problems for recognition. Recently, robust sparse coding achieves the state-of-the-art performance, especially when dealing with occluded images. However, robust sparse coding is known that only guarantee the coefficient is global spa...

We propose a variable-length signature for nearduplicate image matching in this paper. An image is represented by a signature, the length of which varies with respect to the number of patches in the image. A new visual descriptor, viz. Probabilistic Center-symmetric Local Binary Pattern (PCSLBP), is proposed to characterize the appearance of each i...

The goal of panel detection is to decompose the comic image into several panels (or frames), which is the fundamental step to produce digital comic books that are suitable for reading on mobile devices. The existing methods are limited in presenting the extracted panels as squares or rectangles and solely use one type of visual patterns, which are...

In this paper, we initiate a theoretical study on ${N}$ -expert fusion ( ${N}~\boldsymbol {\geq }~2$ ) in the context of biometric authentication (BA). Optimal fusion weights, which depend on performances and variances of, and correlations among individual base-experts have been found, and we also give and prove some new theorems that serve as the...

In order to alleviate the influence of illumination, pose, expression and occlusion variations in face recognition, in this paper, an effective face recognition method based on discriminative sparse representation is proposed. To solve the problem of these variations, we extract discriminative features which represent for each of the training image...

Text segmentation is an essential pre-processing stage for many systems such as text recognition and word spotting. However, few methods have been published for Arabic text segmentation. In Arabic handwritten documents, separating text into words is challenging due to the enormous different Arabic handwriting styles. In this paper, we present a new...

This paper proposes a novel part-based character recognition method for a new topic of RMB (renminbi bank note, the paper currency used in China) serial number recognition, which is important for reducing financial crime and improving financial market stability and social security. Given an input sample, we first generate a set of local image parts...

This paper introduces new handwritten databases of selected words in the five Middle-Eastern languages of Arabic, Dari, Farsi, Pashto and Urdu. The databases share a common lexicon of forty words that are related to finance and are used in daily life. The five databases have been collected from over 1600 native writers located in four countries. Re...

Comics are popular almost throughout the world. With the help of comic document digitization, it is much easier for people to archive and browse comic works. However, there are still some big challenges along with comic document digitization progress. Among these challenges, comic content adaptation is an important one to be tackled. The existing w...

Mail sorting machines play an important role in postal automation. In this paper, we give a brief overview of mail sorting machines in China Post from a pattern recognition point of view. OCR techniques such as postcode recognition and address recognition are essential for mail sorting machines, which are considered as class imbalance problems in o...

This paper presents a new topic of automatic recognition of bank note serial numbers, which will not only facilitate the prevention of forgery crimes, but also have a positive impact on the economy. Among all the different currencies, we focus on the study of RMB (renminbi bank note, the paper currency used in China) serial numbers. For evaluation,...

A new near-duplicate document image matching approach is proposed. Globally, we model the spatial arrangements of objects in an image. Locally, the micro-patterns within each object are captured. To define a micro-pattern, the VV-nary center-symmetric gray value differences in an image local neighborhood of a variable radius are exploited. A visual...

Graph edit distance is a powerful and flexible method for error-tolerant graph matching. Yet it can only be calculated for small graphs in practice due to its exponential time complexity when considering unconstrained graphs. In this paper we propose a quadratic time approximation of graph edit distance based on Hausdorff matching. In a series of e...

The Restricted Boltzmann machine is a graphical model which has been very successful in machine learning and various applications. Recently lots of attention has been devoted to sparse techniques combining a cardinality potential function and an energy function. In this paper we use a convex cardinality potential function for increasing competition...

A near-duplicate document image matching approach characterized by a graphical perspective is proposed in this paper. Document images are represented by graphs whose nodes correspond to the objects in the images. Consequently, the image matching problem is then converted to graph matching. To deal with the instability of object segmentation, a mult...

In the field of biometric authentication, it is a promising trend to perform score fusion to improve authentication accuracy. Many empirical studies have shown the effectiveness of score fusion; however, some other researchers assert that fusion is not always beneficial. Despite considerable empirical efforts, to the best of our knowledge, the rese...

The retrieval of information from scanned handwritten documents is becoming vital with the rapid increase of digitized documents, and word spotting systems have been developed to search for words within documents. These systems can be either template matching algorithms or learning based. This paper presents a coherent learning based Arabic handwri...

Document segmentation is the process of dividing a document (handwritten or printed) into its base components (lines, words, characters). Once the zones (text and non-text) have been identified, the segmentation of the text elements can begin. Several challenges exist which need to be worked out in order to segment the elements correctly. For line...

Separation of keywords from non-keywords is the main problem in keyword spotting systems which has traditionally been approached by simplistic methods, such as thresholding of recognition scores. In this paper, we analyze this problem from a machine learning perspective, and we study several standard machine learning algorithms specifically in the...

The affinity propagation (AP) clustering algorithm has received much attention in the past few years. AP is appealing because it is efficient, insensitive to initialization, and it produces clusters at a lower error rate than other exemplar-based methods. However, its single-exemplar model becomes inadequate when applied to model multisubclasses in...

Large amounts of handwritten documents have been digitized, and the need to search and index these documents is increasing to make them more accessible. Different word spotting systems have been proposed to search for words for this purpose. Since the precision of the word spotting system is crucial, verifying the results of a word spotting system...

Historical documents pose challenging problems for training handwriting recognition systems. Besides the high variability of character shapes inherent to all handwriting, the image quality can also differ greatly, for instance due to faded ink, ink bleed-through, wrinkled and stained parchment. Especially when only few learning samples are availabl...

Facing high error rates and slow recognition speed for full text transcription of unconstrained handwriting images, keyword spotting is a promising alternative to locate specific search terms within scanned document images. We have previously proposed a learning-based method for keyword spotting using character hidden Markov models that showed a hi...

The study of RMB (renminbi bank note, the paper currency used in China) serial number recognition draws more and more attention in recent years, for reducing financial crime, improving financial market stability and social security. The accuracy of RMB recognition relies heavily on the extraction, which is a challenging problem due to background va...

The issue of near duplicate document image retrieval is addressed in this paper, which is characterized by not only encoding each individual word in the image but also modeling its local spatial configuration. On representing each word in the image as a string in terms of its shape characteristics, a lexicon is first learnt from a training set. The...

Text segmentation is an essential pre-processing step for many methods of recognition and for spotting systems as well. There are some characteristics in Arabic that differentiates it from Latin-based scripts. In this thesis proposal, we address the challenges of segmenting offline Arabic handwritten text. Our proposed approach of text segmentaion...

The recognition of unconstrained handwriting images is usually based on vectorial representation and statistical classification. Despite their high representational power, graphs are rarely used in this field due to a lack of efficient graph-based recognition methods. Recently, graph similarity features have been proposed to bridge the gap between...

Aiming at improving the reliability of a recognition system, this paper presents a novel SVM-based rejection measurement (SVMM) and voting based combination methods of multiple classifier system (MCS) for pattern rejection. Compared with the previous heuristic designed criteria, SVMM is more straight-forward and can make use of much more informatio...

In this paper we propose a new approach for dynamic selection of ensembles of classifiers. Based on the concept named multistage organizations, the main objective of which is to define a multi-layer fusion function adapted to each recognition problem, we propose dynamic multistage organization (DMO), which defines the best multistage structure for...

In spite of over two decades of intense research, illumination and pose invariance remain prohibitively challenging aspects of face recognition for most practical applications. The objective of this work is to recognize faces using video sequences both ...

The removal of noise patterns in handwritten images requires careful processing. A noise pattern belongs to a class that we have either seen or not seen before. In the former case, the difficulty lies in the fact that some types of noise patterns look similar to certain characters or parts of characters. In the latter case, we do not know the class...

Norte Av. NS15 s/n Bl. II sala 21, Palmas (TO) 77001-090, Brazil b É cole de Technologie Supérieure (ETS), 1100 Notre-dame ouest, Montréal (QC), Canada H3C-1K3 a b s t r a c t In this work, we propose the LoGID (Local and Global Incremental Learning for Dynamic Selection) framework, the main goal of which is to adapt hidden Markov model-based patte...

We present a statistical hypothesis testing method for handwritten word segmentation algorithms. Our proposed method can be used along with any word segmentation algorithm in order to detect over-segmented or under-segmented errors or to adapt the word segmentation algorithm to new data in an unsupervised manner. The main idea behind the proposed a...

In recognition of Off-line handwritten characters and signatures, stroke extraction is often a crucial step. Given the large number of Chinese handwritten characters, pattern matching based on structural decomposition and analysis is useful and essential to Off-line Chinese recognition to reduce ambiguity. Two challenging problems for stroke extrac...

With the ever-increasing amounts of published materials being made available, developing efficient means of locating target items has become a subject of significant interest. Among the approaches adopted for this purpose is word spotting, which enables the identification of documents through the use of pertinent keywords. This paper reports on an...

Matching pedestrians across disjoint camera views is a challenging task, since their observations are separated in time and space and their appearances may vary considerably. Recently, some approaches of matching pedestrians have been proposed. However, these approaches either used too complex representations or only considered the color informatio...

A novel super-resolution approach is presented. An image pyramid has been built based on the framework of wavelet transform, and the detailed coefficients are explored for training the neural networks. The initial high resolution image is estimated by the trained networks and the inverse wavelet transform, and then is constrained with prior knowled...

Robust segmentation of an iris image plays an important role in iris recognition. However, the nonlinear deformations, pupil dilations, head rotations, motion blurs, reflections, nonuniform intensities, low image contrast, camera angles and diffusions, and presence of eyelids and eyelashes often hamper the conventional iris/pupil localization metho...

A pattern recognition system mainly contains two functional parts, i.e. feature extraction and pattern classification. The success of such a system depends on not only the effectiveness of each of them, but also their operation in concert. The feature extraction process in a traditional recognition system has two major tasks, namely, to extract def...

A new algebraic feature extraction method for image recognition is presented. The optimal transform of image matrices is proposed to extract the features from images. The Frobenius norm of matrices is first introduced as a measure of the distance between two matrices. Based on this, the within-class and between-class distances of image samples are...

Increasing amount of paper documents are produced and received by many organizations. Frequently, they have to be digitized for electronic archiving and later information retrieval or data mining, requiring scanning and OCR. Since OCR techniques are language dependent, the language of the original document must be identified first by advanced techn...

This paper presents a hybrid model of integrating the synergy of two superior classifiers: Convolutional Neural Network (CNN) and Support Vector Machine (SVM), which have proven results in recognizing different types of patterns. In this model, CNN works as a trainable feature extractor and SVM performs as a recognizer. This hybrid model automatica...

This paper presents a robust method for handwritten text line extraction. We use morphological dilation with a dynamic adaptive mask for line extraction. Line separation occurs because of the repulsion and attraction between connected components. The characteristics of the Arabic script are considered to ensure a high performance of the algorithm....

This paper presents a novel approach to recognize images based on nonlinear wavelet approximation. The mathematical theory on nonlinear wavelet approximation is introduced, which shows that nonlinear approximation contains much more information of the original image than linear approximation. Based on this theory, a scheme to obtain the basic infor...

This paper proposes a novel approach named Compressed Submanifold Multifactor Analysis (CSMA) to concisely and precisely deal with multifactor analysis. Compared to the state-of-the-art MPCA method that loses the original local geometry structures of input factors due to the averaging process, our proposed approach can preserve their original geome...

A document image matching approach making use of probabilistic graphical models is proposed. The document image is first represented by a tree with the nodes in the tree corresponding to the regions in the image and the edges indicating the parent-child relationships between them, transforming the problem to tree matching. A graphical model, i.e. p...

One of the most important script groups, which is based on Arabic alphabet, is the Persian/Farsi script. This script is the basis of different languages used in Middle East and Central Asian regions. For the development of Farsi handwritten word recognition systems, the CENPARMI group designed and collected a database. Based on statistical features...

A new approach to extraction of affine invariant features of contour image and matching strategy is proposed for shape recognition. Firstly, the centroid distance and azimuth angle of each boundary point are computed. Then, with a prior-defined angle interval, all the points in the neighbor region of the sample point are considered to calculate the...

For digital images and patterns under the nonlinear geometric transformation, T: (ξ, η) → (x, y), this study develops the splitting algorithms (i.e., the pixel-division algorithms) that divide a 2D pixel into N × N subpixels, where N is a positive integer chosen as N = 2k(k ≥ 0) in practical computations. When the true intensity values of pixels ar...

The size-orientation-invariance characteristic plays an important role in pattern recognition. It has many applications in computer vision, optical character recognition (OCR), office automation, electronic publication, graphics, etc. In this paper, a new method called transformation-ring-projection (TRP) is proposed to achieve this characteristic....

A fast support vector machine (SVM) training algorithm is proposed under SVM's decomposition framework by effectively integrating kernel caching, digest and shrinking policies and stopping conditions. Kernel caching plays a key role in reducing the number of kernel evaluations by maximal reusage of cached kernel elements. Extensive experiments have...

This paper presents linear and bilinear shape transformations including basic transformations, analyzes their geometric properties, and provides computer algorithms. The shape transformations can be used to simplify the recognition of Roman letters, Chinese characters and other pictorial patterns by normalizing their shapes to the standard forms. I...

As a result of its central role in the preprocessing of image patterns, or because of its intrinsic appeal, the design of skeletonization algorithms has been a very active research area. However, few attempts have been made to evaluate the performance of different skeletonization algorithms. This paper presents the results of experiments to evaluat...

Two types of techniques are usually adopted in language differentiation: token matching and statistical analysis. In this paper we present a method which uses a combined analysis of several discriminating statistical features, for the differentiation between European and oriental language scripts. When applied to more than 23 languages, it has prov...

In this paper a methodology for feature selection for the handwritten digit string recognition is proposed. Its novelty lies in the use of a multiobjective genetic algorithm where sensitivity analysis and neural network are employed to allow the use of a representative database to evaluate fitness and the use of a validation database to identify th...

This paper describes a novel method for edge feature detection of document images based on wavelet decomposition and reconstruction. By applying the wavelet decomposition technique, a document image becomes a wavelet representation, i.e. the image is decomposed into a set of wavelet approximation coefficients and wavelet detail coefficients. Discar...

Whilst the design of skeletonization algorithms has been a very active research area, methodologies for an automatic evaluation of the quality of the results remain to be developed. The difficulty rests on the fact that certain geometric properties considered desirable in skeletons (especially for pattern recognition applications) are not easily qu...

Due to different writing styles and various kinds of noise, the recognition of handwritten numerals is an extremely complicated problem. Recently, a new trend has emerged to tackle this problem by the use of multiple classifiers. This method combines individual classification decisions to derive the final decisions. This is called "Combination of M...

This paper includes a description of 3 affiliated oriental languages: Chinese, Japanese, and Korean. It includes a description of the origins of these 3 languages and the inter-relationship among them. Drawn from the viewpoints of several experienced researchers in the field of OCR (Optical Character Recognition) and computational linguistics, it a...

Most state-of-the-art iris recognition algorithms claim to perform with a very high recognition accuracy in a strictly controlled environment. However, their recognition accuracies significantly decrease when the acquired images are affected by different noise factors including motion blur, camera diffusion, head movement, gaze direction, camera an...

A graph matching approach is proposed to retrieve envelope images from a large image database. First, the graph representation of an envelop image is generated based on the image segmentation results, in which each node corresponds to one segmented region. The attributes of nodes and edges in the graph are described by characteristics of the envelo...

A vast number of historical and badly degraded document images can be found in libraries, public, and national archives. Due to the complex nature of different artifacts, such poor quality documents are hard to read and to process. In this paper, a novel adaptive binarization algorithm using ternary entropy-based approach is proposed. Given an inpu...

Advances in digital technology have greatly facilitated the design of new type fonts. Today, hundreds of thousands of fonts can be found in various visual appearances or styles, which are used in digital publishing and information display. As a result, it has become important to find ways of evaluating their impact on our daily lives: (1) ease in r...

In this paper, we will present a novel framework of utilizing periocular region for age invariant face recogni-tion. To obtain age invariant features, we first perform preprocessing schemes, such as pose correction, illumina-tion and periocular region normalization. And then we ap-ply robust Walsh-Hadamard transform encoded local bi-nary patterns (...

In this paper we propose a novel Contourlet Appearance Model (CAM) that is more accurate and faster at localizing facial landmarks than Active Appearance Models (AAMs). Our CAM also has the ability to not only extract holistic texture information, as AAMs do, but can also extract local texture information using the Nonsubsampled Contourlet Transfor...

In document recognition, it is often important to obtain high accuracy or reliability and to reject patterns that cannot be classified with high confidence. This is the case for applications such as the processing of financial documents in which errors can be very costly and therefore far less tolerable than rejections. This paper presents a new ap...

More and more fonts have sprung up in recent years in digital publishing industry and reading devices. In this paper, we focus on methods of evaluating digital Chinese fonts and their typeface characteristics to seek a good way to enhance the character recognition rate. To accomplish this, we combined psychological analysis methods with statistical...

In order to spot the digits in a handwritten document, each component is sent to a classifier. This is a time consuming process because a document usually contains several hundred components. A method is presented to reduce the number of candidate components from a handwritten document sent to the classifier. Furthermore, since the classifier does...

A face image can be represented by a combination of large-and small-scale features. It is well-known that the variations of illumination mainly affect the large-scale features (low-frequency components), and not so much the small-scale features. Therefore, in relevant existing methods only the small-scale features are extracted as illumination-inva...

Quotient Image (QI) algorithm has been widely used in face recognition and re-rendering under varying illumination conditions. One of the inaccuracies of QI algorithm is the assumption of “Ideal Class”, that all faces have the same surface normal (3D shape). However, in practice this assumption is often not true. To reduce the inaccuracy, the Non-I...

We present algorithms for iris segmentation, feature extraction and selection, and iris pattern matching. To segment the inner boundary from a nonideal iris image, we apply a level set based curve evolution approach using the edge stopping function, and to detect the outer boundary, we employ the curve evolution approach using the regularized Mumfo...

Continuous efforts have been made to process degraded iris images for enhancement of the iris recognition performance in unconstrained situations. Recently, many researchers have focused on developing the iris segmentation techniques, which can deal with iris images in a non-cooperative environment where the probability of acquiring unideal iris im...