Imdad Ali Ismaili

Biometric attendance system

This research work has application for attendance system of employers and students in general. The system will facilitate institutions/ organization to make attendance individual in time along with data information thumb impression will be taken as a signature for the system entry. Main design and challenge in this system is the design of database architecture and its business logic.

Supervised method for blood vessel segmentation from coronary angiogram images using 7-D feature vector

With the recent advancement in medical image processing field and sophisticated simulation tools it has been possible to acquire useful information from raw images for different parts of the body. Coronary artery segmentation is the fundamental component which extract significant features from angiogram images. Cardiac catheterization is an invasive diagnostic procedure that provides important information about the structure and function of heart. The procedure usually involves X-ray images of heart, arteries using coronary angiography. The resultant images (coronary angiogram) are considered as best of way to diagnose cardiac heart disease. The main focus of coronary angiography is to find the blockage in major blood vessels, however if the blockage is not found in large blood vessels and patient persists to have pain (angina) then it is concluded that the patient is having micro vascular disease (MVD). MVD is caused by blockage or narrowing of small blood vessels in heart, unfortunately there is no specific test to diagnose MVD but it is common in people having diabetes and blood pressure. This paper proposes an automated method of vessel segmentation from coronary angiogram images using radial basis function and moment invariant-based features to extract the small blood vessel for diagnosis of MVD. Experimental results show that the proposed method is capable of extracting small blood vessels from coronary artery and can be a basis to identify key characteristics for MVD. The dataset of angiogram images have been provided by ISRA University Hospital and MATLAB is used for implementing the proposed method.

Identifying and resolving disorientation in e-learning systems

Web-based learning has been one of the most researched areas for the past two decades. Among different problems encountered in e-learning research, an important phenomenon is disorientation. It is the event which results in learners losing their sense of direction in hyperspace or unknowingly deviating from their learning goal. In this paper we review some e-learning systems and their support for identifying or resolving disorientation. We then present architecture of proposed system with an embedded Disorientation Module (DM). DM consists of sub components namely Sensing Module, Resolution Module and Evaluation Module with subsequent techniques for identifying and resolving various types of disorientation. The paper concludes with suggestions regarding future research directions.

Phonetic-based Sindhi spellchecker system using a hybrid model

This article presents a novel architecture using a hybrid model for developing a Sindhi spellchecker system which has yet not been developed prior to this work. The compound textual forms and glyphs of Sindhi language presents a substantial challenge for developing a Sindhi spellchecker system and generating a similar suggestion list for misspelled words. In order to implement such a system, phonetic-based Sindhi language rules and patterns must be taken into account for increasing the accuracy and efficiency. In this research work, a simple and efficient combinational hybrid system is proposed, using three different algorithms, the Edit Distance algorithm to find the measure of similarity between two Sindhi strings. The phonetic-based SoundEx and ShapeEx algorithms are developed for pattern or glyph matching, generating accurate and an efficient suggestion list for incorrect or misspelled Sindhi words. The proposed system is established with a blend between Phonetic-based SoundEx algorithm and ShapeEx algorithm for pattern or glyph matching, generating accurate and efficient suggestion list for incorrect or misspelled Sindhi words. In this article, a table of phonetically similar-sounding Sindhi characters is presented which are grouped together along with another table containing similar glyph or shape-based character groups. The system has been successfully integrated into a pre-developed Sindhi word processer application. The Sindhi word segmentation methodology and algorithms required for the spellchecker has already been published and so are not discussed in detail in this article.

A framework for retinal vessel segmentation from fundus images using hybrid feature set and hierarchical classification

Retinal blood vessels play an imperative role in detection of many ailments, such as cardiovascular diseases, hypertension, and diabetic retinopathy. The automated way of segmenting vessels from retinal images can help in early detection of many diseases. In this paper, we propose a framework based on hybrid feature set and hierarchical classification approach to segment blood vessels from digital retinal images. Firstly, we apply bidirectional histogram equalization on the inverted green channel to enhance the fundus image. Six discriminative feature extraction methods have been employed comprising of local intensities, local binary patterns, histogram of gradients, divergence of vector field, high-order local autocorrelations, and morphological transformation. The selection of feature sets has been carried out by classifying vessel and background pixels using random forests and evaluating the segmentation performance for each category of features. The selected feature sets are then used in conjunction with our proposed hierarchical classification approach to segment the vessels. The proposed framework has been tested on the DRIVE, STARE, and CHASEDB1 which are the benchmark datasets for retinal vessel segmentation methods. The results obtained from the experimental analysis show that the proposed framework can achieve better results than most state-of-the-art methods.

Speech enabled algorithm for multilingual educational game

In this paper we propose an algorithmii that utilizes the Artificial Intelligence bcased techniques including Heuristic Search and natural language processing to enable tlhe single user to plaiy the game at any time with the coimputer withoutt waiting far the availability of other player. As well as we propose to acldd tlhe support of the vocabularv oJ other regional languages such as Urdu / Sindhi/ Paslhto witha the speech synthesis based pronunciation facility. Thae tools and tlhe technologies that are to be used for the implemtientation of the algorithm include: Microsoft VB and AI Techniques along with mttultilingual dictioncaries. The imtplemlentation of this algoritlhm wouldfacilitate any one in general and studcents in particulair to butild a strong ivocabulary of acny language with just the fun of playing. Thlis wouild provide a direct contriburtion to thze educcation an1d literacyaclong with entertainment.