دانلود رایگان مقاله آرم و مهر بر بازیابی تصویر سند اداری

Abstract

With the advance of technology, business offices and organizations together with their clients create a massive amount of administrative documents every day. Administrative documents commonly contain some salient entities such as logos, stamps or seals as the means of their authentication and proprietorship. These salient entities provide quite discriminative information, which can effectively be used for different tasks of document image retrieval, classification and recognition in document-based applications. Thus, proper detection/recognition of these entities in document images increases the performance of such applications in terms of document retrieval, classification, and recognition. To present the state-of-the-art research on the retrieval of administrative document images, this paper deals with a survey of administrative document image retrieval in relation to seals and logos. All the available datasets, feature extraction and classification techniques for logo and seal detection/recognition are discussed systematically. The shortcomings of the present technologies on logo and seal based document processing are also highlighted. Avenues of the future works are further given for the benefit of readers. To the best of authors’ knowledge, there is no survey on administrative document image retrieval and hence the authors hope that this work will be helpful to the researchers of the document analysis community.

9. Conclusion and future directions

In spite of considerable amount of work afforded for logo and seal detection/spotting in the literature, this problem still needs more efforts and research. Since detection/spotting result has direct effect to the recognition/retrieval accuracy, it is reasonable to have a feedback from the recognition/retrieval step to the detection/spotting step allowing the detection step to correct itself. Therefore, developing strategies, which consider both the problems of detection/spotting and recognition/retrieval in a single framework using some feedback policies, can improve the overall system performance. In such a scenario, the recognition task must be accomplished quickly in the presence of geometric transformation, noise, over/under segmentation and possible occlusion [5,75].