The invention discloses an iris image quality cascade type evaluation method. The method includes following steps: S1, measuring and calculating the relative position between a light source image point and a pupil in an iris image, determining whether strabismus exists, determining the image fails to satisfy the quality requirement if yes, and continuing if not; S2, detecting the availability of an iris in the iris image according to a grayscale classification statistical method, determining whether the availability is qualified, determining the image fails to satisfy the quality requirement if not, and continuing if yes; S3, measuring and calculating the local energy gradient in the iris image, determining whether defocus blur exists, determining the image fails to satisfy the quality requirement if yes, and continuing if not; and S4, determining whether motion blur exists according to a circular gradient peak value detection method, determining the image fails to satisfy the quality requirement if yes, and determining the image satisfies the quality requirement if not. According to the technical scheme, the design of a multi-thread assembly line is facilitated, the quality evaluation time is effectively reduced, the storage consumption is reduced, and the iris recognition efficiency is improved.