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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/55506


    Title: 基於三元化樣式的通用型區域特徵描述方法
    Other Titles: A Universally Applicable Feature Descriptor Based on Local Ternary Patterns
    Authors: 廖文宏
    Contributors: 國立政治大學資訊科學系
    行政院國家科學委員會
    Keywords: 三元化樣式;通用型;區域特徵
    Date: 2011
    Issue Date: 2012-11-12 11:06:00 (UTC+8)
    Abstract: 區域二元化樣式與其各種變型被廣泛應用於物件辨識中的特徵描述，然而現有的區域特徵描述方式，普遍存在適用時機的問題，也就是針對不同類型的圖像資料庫，必須選用符合該圖片性質的描述法，方能達到較佳的辨識效果，舉例而言，處理材質影像時多使用uniform pattern，而進行人臉偵測或表情辨識時則多採用一般型的區域二元化樣式，先前我們所定義的延展式區域三元化樣式，也呈現同樣的狀況。本研究的目標是建構一個通用型的區域三元化樣式，使其一體適用於各類圖型辨識的任務，我們將以先前定義的延展式區域三元化樣式為基礎，探討各種降維演算法的結合機制，並提出可行的樣式定義方法，我們將針對ETLP 中的uniform pattern定義重新思考，藉由大規模實驗與統計，探討各類uniform pattern 的從屬關係與出現比例，並依據比例原則，在降維階段分配適當之維度，稱之為比例式降維法。我們將研究藉由比例式降維法所產生的特徵描述子的特性，並針對其抗噪性、描述力與通用性進行深度的分析與廣泛的實驗，以檢驗此類圖像描述方法之效能。我們也預計將三元化及比例式降維的概念，套用至區域二元化樣式的各種變型，以定義更多樣化的區域圖像描述方法。
    Local binary pattern and its derivatives have been widely employed to represent low-level features in many pattern recognition tasks. However, existing local descriptors fail to achieve universal applicability in the sense that specific types of local binary patterns are better suited for certain collections of images. For example, uniform local binary patterns are preferred when dealing with textures, while regular local binary patterns are adopted for face detection and facial expression recognition. The same phenomenon is also observed in the extended local ternary pattern proposed by the author. We propose to design a universally applicable local descriptor based on the extended local ternary pattern to address the above concern. We will examine the dimensionality reduction techniques for local binary/ternary patterns. We will exploit the feasibility of combining dimensionality reduction approaches to derive a novel local descriptor that is suitable for all kinds of object recognition applications. Specifically, we will investigate all possible definitions of uniform patterns under ternary encoding scheme and study their properties. We will devise a dimensionality assignment algorithm in which the allocated dimension is proportional to the appearance rate of the corresponding pattern group. The newly defined extend local ternary pattern using commensurate dimensionality reduction (ELTP-CDR) technique will be extensively tested to analyze its universality, discriminability, and noise sensitivity. We will also utilize the concepts of ternarization and commensurate dimensionality reduction to various derivatives of local binary pattern to generate more versatile local descriptors.
    Relation: 商品化
    學術補助
    研究期間:10008~ 10107
    研究經費:489仟元
    Data Type: report
    Appears in Collections:[資訊科學系] 國科會研究計畫

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