Browsing by Author "Assabie, Yaregal (PhD)"

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    Amharic Document Categorization Using Itemsets Method
    (Addis Ababa University, 2013-02) Hailu, Abraham; Assabie, Yaregal (PhD)
    Document categorization or document classification is the process of assigning a document to one or more classes or categories. Many researches are conducted in the area of Amharic document categorization. The main focus of those studies is to examine different document categorization techniques and measuring their performance however itemsets method is not so far examined. This study focused to extend Apriori algorithm which is traditionally used for the purpose of knowledge mining in the form of association rules. The research focused on the basic principles of applying itemsets method to categorize Amharic documents. In addition to that the implementation of all the required tools which helps to carry out automatic Amharic Document categorization using itemsets method is developed and the algorithm is examined. Experiment results show itemsets method is an efficient method to categorize Amharic documents. The effectiveness and accuracy of the method to categorize Amharic documents is also evaluated and reported. Finally, factors affecting the performance of the proposed system and the importance of preprocessing training dataset in finding useful information are discussed.
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    Amharic Document Categorization Using Itemsets Method
    (Addis Ababa University, 2013-02) Hailu, Abraham; Assabie, Yaregal (PhD)
    Document categorization or document classification is the process of assigning a document to one or more classes or categories. Many researches are conducted in the area of Amharic document categorization. The main focus of those studies is to examine different document categorization techniques and measuring their performance however itemsets method is not so far examined. This study focused to extend Apriori algorithm which is traditionally used for the purpose of knowledge mining in the form of association rules. The research focused on the basic principles of applying itemsets method to categorize Amharic documents. In addition to that the implementation of all the required tools which helps to carry out automatic Amharic Document categorization using itemsets method is developed and the algorithm is examined. Experiment results show itemsets method is an efficient method to categorize Amharic documents. The effectiveness and accuracy of the method to categorize Amharic documents is also evaluated and reported. Finally, factors affecting the performance of the proposed system and the importance of preprocessing training dataset in finding useful information are discussed.
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    Design and Implementation of Automatic Student Evaluation form Processing System Using Image Analysis Techniques
    (Addis Ababa University, 2011-06) Shumeye, Demeke; Assabie, Yaregal (PhD)
    Addis Ababa University (AAU) is one of the largest universities in Ethiopia. It has more than sixty thousand students and more than two thousand academic staffs. To know the teaching effectiveness of the academic staff and to get the student views regarding the teaching performance of instructors, the university has prepared a questionnaire form, which contains about 36 statements that will be filled by students. These forms are processed manually in such a way that the values given by the students for each statement are added and the average values are computed. Then these values are divided by the total number of students to get the total average values given by all the students. Processing the student evaluation form manually for a large number of students makes the processing of the forms tedious, time taking and error prone. To alleviate this problem a mechanism has to be developed by using different form processing techniques. In this project a digital image analysis technique is used to process the form. For this project, MATLAB is used as a programming tool since it is high-performance language for technical computing that integrates computation, visualization, and programming where problems and solutions are expressed in mathematical notation. The system is designed to recognize only the values encircled by the students against each statement. After the document is scanned a template image is taken from the normalized gradient field of the image. Gradient is the change in gray level with direction. This can be calculated by taking the difference in value of neighboring pixels, producing a vector for each pixel. Thus, the gradient field of the image is normalized with a certain threshold value. Noise is removed while computing the gradient field of the image. Template matching image analysis technique is used, to detect regions which contain choices against each statement. Then, values encircled by the students are detected by finding relative circles having a range of radius in the detected region. The coordinate values of the detected circles are used to recognize values encircled by the students. Finally, recognized values for each statement are added and the average values are computed. Then these values are divided by the total number of students to get the total average values given by all the students. Keywords: Addis Ababa University, Student evaluation form, Template matching, Recognition
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    Design and Implementation of Automatic Student Evaluation form Processing System Using Image Analysis Techniques
    (Addis Ababa University, 2011-06) Shumeye, Demeke; Assabie, Yaregal (PhD)
    Addis Ababa University (AAU) is one of the largest universities in Ethiopia. It has more than sixty thousand students and more than two thousand academic staffs. To know the teaching effectiveness of the academic staff and to get the student views regarding the teaching performance of instructors, the university has prepared a questionnaire form, which contains about 36 statements that will be filled by students. These forms are processed manually in such a way that the values given by the students for each statement are added and the average values are computed. Then these values are divided by the total number of students to get the total average values given by all the students. Processing the student evaluation form manually for a large number of students makes the processing of the forms tedious, time taking and error prone. To alleviate this problem a mechanism has to be developed by using different form processing techniques. In this project a digital image analysis technique is used to process the form. For this project, MATLAB is used as a programming tool since it is high-performance language for technical computing that integrates computation, visualization, and programming where problems and solutions are expressed in mathematical notation. The system is designed to recognize only the values encircled by the students against each statement. After the document is scanned a template image is taken from the normalized gradient field of the image. Gradient is the change in gray level with direction. This can be calculated by taking the difference in value of neighboring pixels, producing a vector for each pixel. Thus, the gradient field of the image is normalized with a certain threshold value. Noise is removed while computing the gradient field of the image. Template matching image analysis technique is used, to detect regions which contain choices against each statement. Then, values encircled by the students are detected by finding relative circles having a range of radius in the detected region. The coordinate values of the detected circles are used to recognize values encircled by the students. Finally, recognized values for each statement are added and the average values are computed. Then these values are divided by the total number of students to get the total average values given by all the students. Keywords: Addis Ababa University, Student evaluation form, Template matching, Recognition
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    Recognition of Double Sided Amharic Braille Documents
    (Addis Ababa University, 2015-11) Seid, Hassen; Assabie, Yaregal (PhD)
    Amharic language has large number of characters. As a result, Amharic Braille image recognition into print text is not an easy task. Amharic Braille cell formulation, encoding to a Braille code and translating the code to print text are different from Braille recognition systems of foreign languages’ characters. Few researches have been conducted in recognition of Amharic Braille documents. However, recognition of double sided Amharic Braille documents, which needs segmentation and identification of recto and verso dots from the background, and separation of overlapping recto and verso dots, has not been conducted so far. In this work, we propose a design for recognition of double sided Amharic Braille documents. The design has a preprocessing, segmentation, dot identification, page formulation, transformation, and recognition components. We used direction field tensor to preprocess and segment dots from the background. After segmentation, gradient field is used to identify a dot as recto or verso. Overlapping dots were further segmented and identified using Braille dot attributes (centroid, orientation, and area). The identified recto and verso dots are separated into two separate images or pages using the page formulation component. Then, we used Braille cell encoding algorithm in order to formulate identified recto or verso dots into a Braille code. Finally, the Braille code is translated to print text using Braille code translation algorithm. The designed algorithms encode and translate the dots starting from left-top corner of the first dot to the right downward over the page. In order to use the same Braille cell encoding and Braille code translation algorithms for both pages, dots on the recto page are mirrored about a vertical symmetric line. Moreover, we used rotation in reversing wrongly scanned documents automatically as long as the translation performance is less than some threshold value which notifies the system the page is wrongly scanned. In order to test the proposed design, we developed a prototype using MATLAB and test performances of dot identification and translation of double sided Amharic Braille images to print texts. We achieved an average dot identification accuracy of 99.3% and average translation accuracy of 95.6%. This is remarkably motivating performance as it is the first achievement in recognition of double sided Amharic Braille documents. Key Words: - Braille Cell, Direction Field Tensor, Gradient Field, Recto Dot and Verso Dot.
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    Recognition of Double Sided Amharic Braille Documents
    (Addis Ababa University, 2015-11) Seid, Hassen; Assabie, Yaregal (PhD)
    Amharic language has large number of characters. As a result, Amharic Braille image recognition into print text is not an easy task. Amharic Braille cell formulation, encoding to a Braille code and translating the code to print text are different from Braille recognition systems of foreign languages’ characters. Few researches have been conducted in recognition of Amharic Braille documents. However, recognition of double sided Amharic Braille documents, which needs segmentation and identification of recto and verso dots from the background, and separation of overlapping recto and verso dots, has not been conducted so far. In this work, we propose a design for recognition of double sided Amharic Braille documents. The design has a preprocessing, segmentation, dot identification, page formulation, transformation, and recognition components. We used direction field tensor to preprocess and segment dots from the background. After segmentation, gradient field is used to identify a dot as recto or verso. Overlapping dots were further segmented and identified using Braille dot attributes (centroid, orientation, and area). The identified recto and verso dots are separated into two separate images or pages using the page formulation component. Then, we used Braille cell encoding algorithm in order to formulate identified recto or verso dots into a Braille code. Finally, the Braille code is translated to print text using Braille code translation algorithm. The designed algorithms encode and translate the dots starting from left-top corner of the first dot to the right downward over the page. In order to use the same Braille cell encoding and Braille code translation algorithms for both pages, dots on the recto page are mirrored about a vertical symmetric line. Moreover, we used rotation in reversing wrongly scanned documents automatically as long as the translation performance is less than some threshold value which notifies the system the page is wrongly scanned. In order to test the proposed design, we developed a prototype using MATLAB and test performances of dot identification and translation of double sided Amharic Braille images to print texts. We achieved an average dot identification accuracy of 99.3% and average translation accuracy of 95.6%. This is remarkably motivating performance as it is the first achievement in recognition of double sided Amharic Braille documents. Key Words: - Braille Cell, Direction Field Tensor, Gradient Field, Recto Dot and Verso Dot.