Automatic Table Recognition and Extrac-tion from Heterogeneous Documents

Abstract This paper examines automatic recognition and extraction of tables from a large collection of heterogeneous documents. The heterogeneous documents are initially pre-processed and converted to HTML codes, after which an algorithm recognises the table portion of the documents. Hidden Markov Model (HMM) is then applied to the HTML code in order to extract the tables. The model was trained and tested with five hundred and twenty six self-generated tables (three hundred and twenty-one (321) tables for training and two hundred and five (205) tables for testing). Viterbi algorithm was implemented for the testing part. The system was evaluated in terms of accuracy, precision, recall and f-measure. The overall evaluation results show 88.8% accuracy, 96.8% precision, 91.7% recall and 88.8% F-measure revealing that the method is good at solving the problem of table extraction

An Appraisal of Content-Based Image Retrieval (CBIR) Methods

Background: Content Based Image Retrieval (CBIR) is an aspect of computer vision and image processing that finds images that are similar to a given query image in a large scale database using the visual contents of images such as colour, texture, shape, and spatial arrangement of regions of interest (ROIs) rather than manually annotated textual keywords. A CBIR system represents an image as a feature vector and measures the similarity between the image and other images in the database for the purpose of retrieving similar images with minimal human intervention. The CBIR system has been deployed in several fields such as fingerprint identification, biodiversity information systems, digital libraries, Architectural and Engineering design, crime prevention, historical research and medicine. There are several steps involved in the development of CBIR systems. Typical examples of these steps include feature extraction and selection, indexing and similarity measurement. Problem: However, each of these steps has its own method. Nevertheless, there is no universally acceptable method for retrieving similar images in CBIR. Aim: Hence, this study examines the diverse methods used in CBIR systems. This is with the aim of revealing the strengths and weakness of each of these methods. Methodology: Literatures that are related to the subject matter were sought in three scientific electronic databases namely CiteseerX, Science Direct and Google scholar. The Google search engine was used to search for documents and WebPages that are appropriate to the study. Results: The result of the study revealed that three main features are usually extracted during CBIR. These features include colour, shape and text. The study also revealed that diverse methods that can be used for extracting each of the features in CBIR. For instance, colour space, colour histogram, colour moments, geometric moment as well as colour correlogram can be used for extracting colour features. The commonly used methods for texture feature extraction include statistical, model-based, and transform-based methods while the edge method, Fourier transform and Zernike methods can be used for extracting shape features. Contributions: The paper highlights the benefits and challenges of diverse methods used in CBIR. This is with the aim of revealing the methods that are more efficient for CBIR. Conclusion: Each of the CBIR methods has their own advantages and disadvantages. However, there is a need for a further work that will validate the reliability and efficiency of each of the method

Cassava (Manihot esculenta Crantz) and Yam (Dioscorea spp.) Crops and their derived foodstuffs: Safety, security and nutritional value

Cassava (Manihot esculenta Crantz) and yam (Dioscorea spp.) are tropical crops consumed by ca. 2 billion people and represent the main source of carbohydrate and energy for the approximately 700 million people living in the tropical and sub-tropical areas. They are a guarantee of food security for developing countries. The production of these crops and the transformation into food-derived commodities is increasing, it represents a profitable business and farmers generate substantial income from their market. However, there are some important concerns related to the food safety and food security. The high post-harvest losses, mainly for yam, the contamination by endogenous toxic compounds, mainly for cassava, and the contamination by external agents (such as micotoxins, pesticides, and heavy metal) represent a depletion of economic value and income. The loss in the raw crops or the impossibility to market the derived foodstuffs, due to incompliance with food regulations, can seriously limit all yam tubers and the cassava roots processors, from farmers to household, from small-medium to large enterprises. One of the greatest challenges to overcome those concerns is the transformation of traditional or indigenous processing methods into modern industrial operations, from the crop storage to the adequate package of each derived foodstuff