Эффективные способы и средства описания изображений в задачах распознавания
Диссертация
Глава четыре посвящена практическому исследованию полученных теоретических результатов. Описана библиотека вычисления признаков изображений, программно реализованная в рамках алгоритмическо-программного комплекса для автоматизации научных исследований и обучения в области обработки, анализа, распознавания и понимания изображений «Черный квадрат», приведены характеристики разработанной библиотеки… Читать ещё >
Содержание
- Глава 1. Формальные способы описания изображений
- 1. 1. Исследование моделей изображений
- 1. 1. 1. Понятие модели изображения
- 1. 1. 2. Классификация моделей изображений
- 1. 2. 1. Классы моделей, порождаемые методами когнитивной психологии
- 1. 2. 2. Классы моделей, порождаемые методами представления и обработки изображений
- 1. 2. 3. Классы моделей, порождаемые дескриптивным подходом к анализу и распознаванию изображений
- 1. 2. Роль признаковой модели в задачах распознавания и анализа изображений
- 1. 2. 1. Признаковое описание изображений
- 1. 2. 2. Определение понятия «признак изображения»
- 1. 2. 3. Основные задачи анализа и распознавания изображений, в которых используются признаки изображений
- 1. 1. Исследование моделей изображений
- 2. 1. Основные подходы к классификации признаков изображений
- 2. 1. 1. Библиографические источники, использованные для классификации и систематизации признаков изображений
- 2. 1. 2. Требования к классификации признаков изображений
- 2. 1. 3. Принципы классификации признаков изображений
- 2. 2. Классификации признаков изображений по информации об изображении
- 2. 2. 1. Классификация признаков по типу изображения, служащего основой для вычисления признака
- 2. 2. 1. 1. Бинарные признаки
- 2. 2. 1. 2. Тоновые признаки
- 2. 2. 1. 3. Яркостные признаки
- 2. 2. 2. Классификация признаков по типу модельного представления, служащего основой для вычисления признака изображения
- 2. 2. 2. 1. Статистические признаки
- 2. 2. 2. 2. Признаки, характеризующие форму
- 2. 2. 2. 3. Спектральные признаки
- 2. 2. 3. Классификация признаков по области изображения, на которой вычисляется признак
- 2. 2. 4. Классификация признаков по типу объекта, служащего основой для вычисления признака
- 2. 2. 4. 1. Точечные признаки
- 2. 2. 4. 2. Контурные признаки
- 2. 2. 4. 3. Сегментационные признаки
- 2. 2. 4. 4. Остовные признаки
- 2. 2. 1. Классификация признаков по типу изображения, служащего основой для вычисления признака
- 2. 3. 1. Классификация по уровню признака
- 2. 3. 2. Классификация по способу определения признака
- 2. 3. 2. 1. Вычисляемые признаки
- 2. 3. 2. 2. Измеряемые признаки
- 2. 3. 2. 3. Извлекаемые признаки
- 2. 3. 2. 4. Выделяемые признаки
- 2. 3. 3. Классификация по типу пространства, допустимым элементом которого является признак
- 2. 3. 3. 1. Символы и символьные строки
- 2. 3. 3. 2. Числовые, векторные, матричные признаки
- 2. 3. 3. 3. Структуры
- 2. 3. 3. 4. Кусочно-непрерывные функции 59 2.3.4. Классификация признаков по математическому аппарату, используемому для определения признаков
- 2. 3. 4. 1. Комбинаторные признаки
- 2. 3. 4. 2. Логические признаки
- 2. 3. 4. 3. Матричные признаки
- 2. 3. 4. 4. Арифметические признаки
- 2. 3. 4. 5. Топологические/геометрические признаки 62 2.4. Классификации признаков изображений, основанные на наличии у признаков некоторых специальных свойств
- 3. 1. Математическая постановка задачи распознавания изображений
- 3. 1. 1. Понятие эквивалентности в задачах распознавания изображений и способы задания эквивалентности
- 3. 1. 2. Математическая постановка задачи распознавания изображений в терминах классов эквивалентности
- 3. 1. 3. Математическая постановка редуцированной задачи распознавания изображений
- 3. 1. 4. Условия полноты класса ABO для редуцированной задачи распознавания изображений
- 3. 1. 5. Классы эквивалентности изображений в задачах распознавания
- 3. 2. Мульти-модельные представления изображений в задачах распознавания
- 3. 2. 1. Понятие порождающего дескриптивного дерева
- 3. 2. 2. Параметрические ПДЦ 77 3.2.2.1. Использование параметрических ПДЦ при решении прикладных задач
- 3. 3. Формальное описание метода выбора преобразования изображений в зависимости от информационных характеристик изображений
- 3. 3. 1. Информационные свойства изображений
- 3. 3. 2. Алгоритмическая схема, реализующая метод выбора преобразований изображений в задачах распознавания
- 4. 1. Библиотека вычисления признаков изображений
- 4. 1. 1. Краткая характеристика библиотеки вычисления признаков
- 4. 1. 2. Сценарий работы с библиотекой вычисления признаков
- 4. 2. Применение предложенного метода в задаче диагностического анализа цитологических препаратов
- 4. 2. 1. Постановка задачи анализа цитологических препаратов
- 4. 2. 2. Описание шагов предложенного метода при решении задачи анализа цитологических препаратов
- 4. 2. 3. Сравнение результатов распознавания на различных наборах признаков
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