روشی مطمئن برای مقابله با مشکلات طبقه‌بندی اثر انگشت
محورهای موضوعی : مهندسی برق و کامپیوترفائزه ميرزايي 1 , حسين ابراهيم‌پور کومله 2 , محسن بيگلري 3
1 - دانشگاه کاشان
2 - دانشگاه کاشان
3 - دانشگاه صنعتی شاهرود
کلید واژه: شناسایی اثر انگشت طبقه‌بندی اثر انگشت طبقه‌بندی احتمالی طبقه‌بندی مبتنی بر قانون,
چکیده مقاله :
اثر انگشت بیومتریکی است که به دلیل ویژگی‌های منحصر به فردش، بیشترین کاربرد را در سیستم‌های تشخیص و تعیین هویت داشته است. در سیستم‌های تعیین هویت، تصویر ورودی با تمام تصاویر ثبت‌شده در پایگاه مقایسه می‌گردد و در صورتی که پایگاه داده حجیم باشد، عمل مقایسه بسیار زمان‌بر خواهد بود. برای نمونه می‌توان به پایگاه‌های داده موجود در FBI اشاره نمود. یکی از راه حل‌های تأییدشده برای افزایش سرعت، طبقه‌بندی تصاویر است. در طبقه‌بندی مطلق، به هر اثر انگشت تنها یک کلاس تخصیص می‌یابد. دلایل مختلفی چون نویز یا عدم وجود همه نقاط یکتا در محدوده تصویر، تعیین یک کلاس مطلق برای همه تصاویر را دچار مشکل می‌کند. در این مقاله، روشی جدید بر پایه طبقه‌بندی احتمالی ارائه شده که برای هر تصویر ورودی، مجموعه‌ای از کلاس‌ها مشخص می‌شود که هر یک دارای یک احتمال می‌باشند. در مرحله انطباق، کلاس‌ها به ترتیب اولویتشان جستجو می‌شوند. آزمایشات صورت‌گرفته بر روی پایگاه داده شناخته‌شده 2002 FVC، تأثیر استفاده از طبقه‌بندی احتمالی را به روشنی نشان داده است. با در نظر گرفتن کلاس‌های دوم و سوم تعیین‌شده توسط روش پیشنهادی، دقت شناسایی سیستم تقریباً 18% افزایش یافته است، در صورتی که سرعت آن، 2 تا 3 برابر بیشتر از طبقه‌بندی مطلق می‌باشد.
Fingerprint as a biometric has the most applications in verification and identification systems, because of its specific properties. In identification systems, input image is compared with all of images stored in the database. In huge databases, the comparison will take large amounts of time; Consider FBI databases, for instance. Image classification is one of the approved methods to increase the identification speed. Only one class is assigned to each fingerprint in tradition absolute classification. Various reasons like noise or lack of all the singularity points in captured region, cause the problem in determination of an absolute class for all the images. In this article, a new method based on probabilistic classification is presented. In the proposed approach, a set of classes are considered for each input image with a specific probability. These classes are searched in order of their probabilities priority in matching stage. Experiments on well-known FVC2002 database, exhibit the effect of probable classification clearly. Using only the second and third classes assigned by the proposed method, the identification system achieves about 18% increase in accuracy and 2-3 times speedup in compared to the traditional methods.
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