An image processing apparatus comprising: a first feature value calculation unit adapted to calculate a first feature value for each pixel in an image of mucosal structure picked up with an endoscope adapted to be insertable into a body cavity, where the first feature value represents a value of an index which indicates what shape a local region including a pixel of interest and each pixel in a neighborhood of the pixel of interest has, wherein the first feature value is calculated based on the eigenvalue with the biggest absolute value obtained through computations using a Hesse matrix; a second feature value calculation unit adapted to calculate a degree of concentration of a gradient vector as a second feature value based on the gradient vector defined by a gradient direction and a gradient intensity calculated for each pixel in the image, where the degree of concentration of the gradient vector represents a state of distribution in the local region; an evaluation value calculation unit adapted to calculate a geometric evaluation value for each pixel in the image, where a value which enables distinguishing between a linear mucosal structure and a massive mucosal structure contained in the image and which does not depend on image contrast is calculated as the geometric evaluation value based on calculation results of the first feature value and the second feature value, wherein the geometric evaluation value is calculated by changing an arithmetic expression depending on whether the said eigenvalue is positive or negative; and a region extraction unit adapted to separately extract a candidate region estimated to contain the linear mucosal structure and a candidate region estimated to contain the massive mucosal structure based on a calculation result of the geometric evaluation value. a first feature value calculation unit adapted to calculate a first feature value for each pixel in an image of mucosal structure picked up with an endoscope adapted to be insertable into a body cavity, where the first feature value represents a value of an index which indicates what shape a local region including a pixel of interest and each pixel in a neighborhood of the pixel of interest has, wherein the first feature value is calculated based on the eigenvalue with the biggest absolute value obtained through computations using a Hesse matrix; a second feature value calculation unit adapted to calculate a degree of concentration of a gradient vector as a second feature value based on the gradient vector defined by a gradient direction and a gradient intensity calculated for each pixel in the image, where the degree of concentration of the gradient vector represents a state of distribution in the local region; an evaluation value calculation unit adapted to calculate a geometric evaluation value for each pixel in the image, where a value which enables distinguishing between a linear mucosal structure and a massive mucosal structure contained in the image and which does not depend on image contrast is calculated as the geometric evaluation value based on calculation results of the first feature value and the second feature value, wherein the geometric evaluation value is calculated by changing an arithmetic expression depending on whether the said eigenvalue is positive or negative; and a region extraction unit adapted to separately extract a candidate region estimated to contain the linear mucosal structure and a candidate region estimated to contain the massive mucosal structure based on a calculation result of the geometric evaluation value.