1、會計學1數字圖像處理圖像特征提取數字圖像處理圖像特征提取23顏色形狀紋理；n而對于灰度信息處理，主要講述直方圖技術。45HSV色彩空間YUV色彩空間RGB色彩空間Lab色彩空間XYZ色彩空間678原始彩色圖像紅色分量圖像綠色分量圖像藍色分量圖像910111213原始彩色圖像色調分量圖像飽和度分量圖像亮度分量圖像141516原始彩色圖像Y（亮度）分量圖像U（色度）分量圖像V（濃度）分量圖像1718原始彩色圖像X分量圖像Y分量圖像Z分量圖像192021原始彩色圖像L分量圖像a分量圖像b分量圖像2223CTArray CImageProcessing:Histogram_of_gray_image(

2、 const CTMatrix& gray_image )const long dimension = 256; / 直方圖維數CTArray histogram( dimension ); / 構造直方圖for( int index = 0; index dimension; index + ) / 直方圖遍歷histogram index = 0; long image_height = gray_image.Get_height(); / 圖像高度long image_width = gray_image.Get_width(); / 圖像寬度for( int row = 0; row

3、image_height; row + )for( int column = 0; column image_width; column + ) histogram gray_imagerowcolumn +; return histogram; / 返回直方圖242526272829CTMatrix CImageProcessing:Histogram_equalization( const CTMatrix& gray_image, long equal_scale )long image_height = gray_image.Get_height();long image_width

4、= gray_image.Get_width();CTMatrix result_image( image_height, image_width );CTArray histogram = Normalize_histogram( Histogram_of_gray_image( gray_image ) );for( int index = 1; index histogram.GetDimension(); index + )histogram index += histogram index - 1 ;for( int index = 0; index histogram.GetDim

5、ension(); index + )histogram index = long( long( histogram index * equal_scale ) * ( 256.0 / double( equal_scale ) ) );histogram index = max( 0, histogram index );histogram index = min( 255, histogram index );for( int row = 0; row image_height; row + )for( int column = 0; column image_width; column

6、+ )result_image row column = BYTE( histogram gray_image row column );return result_image;30原始圖像3132333435n部特征（如直線段、圓弧、角點、高曲率點等），以解決遮擋問題。3637Hu不變矩傅里葉描述子Hough變換Zernike不變矩Radon變換383940414243444546474849505152535455CTArray CImageProcessing:Position_from_binary_image( const CTMatrix& binary_image, BlackW

7、hite object_color )long number_of_objects = 0;long image_height = binary_image.Get_height();long image_width = binary_image.Get_width();for( int row = 0; row image_height; row + )for( int column = 0; column image_width; column + )if( binary_image row column = object_color )number_of_objects +;CTArra

8、y array_of_positions( number_of_objects );number_of_objects = 0;for( int row = 0; row image_height; row + )for( int column = 0; column image_width; column + )if( binary_image row column = object_color )array_of_positions number_of_objects .m_re = row;array_of_positions number_of_objects .m_im = colu

9、mn;number_of_objects +;return array_of_positions;56CTMatrix CImageProcessing:Binary_image_from_position( const CTArray& array_of_positions, long image_height, long image_width, BlackWhite object_color )CTMatrix binary_image( image_height, image_width );for( int row = 0; row image_height; row + )for(

10、 int column = 0; column image_width; column + )binary_image row column = ( object_color = White ? Black : White );long dimension = array_of_positions.GetDimension();for( int index = 0; index dimension; index + )long row = long( array_of_positions index .m_re );long column = long( array_of_positions index .m_im );if( binary_image.Is_point_valid( CImagePoint(